modelId
string | author
string | last_modified
timestamp[us, tz=UTC] | downloads
int64 | likes
int64 | library_name
string | tags
sequence | pipeline_tag
string | createdAt
timestamp[us, tz=UTC] | card
string |
|---|---|---|---|---|---|---|---|---|---|
csukuangfj/sherpa-onnx-zipformer-ru-2025-04-20 | csukuangfj | 2025-04-20T15:01:57Z | 0 | 0 | null | [
"onnx",
"region:us"
] | null | 2025-04-20T14:42:12Z | # Introduction
Models in this directory are from
https://huggingface.co/alphacep/vosk-model-ru/tree/main
|
CoexistAI/q-flake | CoexistAI | 2025-04-20T14:59:40Z | 0 | 0 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | 2025-04-20T14:58:43Z | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-flake
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="CoexistAI/q-flake", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
Zer0Cold/Mistral_v0_3_cryptonews | Zer0Cold | 2025-04-20T14:58:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/mistral-7b-v0.3-bnb-4bit",
"base_model:finetune:unsloth/mistral-7b-v0.3-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T14:54:58Z | ---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
license: apache-2.0
language:
- en
---
# Uploaded model
- **Developed by:** Zer0Cold
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
hoanguyenthanh07/Pythera_insert_object | hoanguyenthanh07 | 2025-04-20T14:57:33Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"arxiv:1910.09700",
"region:us"
] | null | 2025-04-20T13:34:33Z | ---
library_name: diffusers
---
# Model Card for Model ID
# Paper :https://huggingface.co/papers/1910.09700
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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[More Information Needed]
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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|
Charmainemahachi/shona-gpt2-tokenizer | Charmainemahachi | 2025-04-20T14:56:36Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T14:56:35Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
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### Downstream Use [optional]
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[More Information Needed]
### Out-of-Scope Use
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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[More Information Needed] |
ppx007/ThisIsNewTmp | ppx007 | 2025-04-20T14:53:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T14:53:06Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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morinoko-inari/ruby-rails-fine-tuned-ja-en | morinoko-inari | 2025-04-20T14:51:51Z | 26 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"base_model:Helsinki-NLP/opus-mt-ja-en",
"base_model:finetune:Helsinki-NLP/opus-mt-ja-en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | 2025-04-19T13:55:49Z | ---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-ja-en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ruby-rails-fine-tuned-ja-en
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ruby-rails-fine-tuned-ja-en
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ja-en](https://huggingface.co/Helsinki-NLP/opus-mt-ja-en).
It achieves the following results on the evaluation set:
- Loss: 1.6714
- Bleu: 0.3300
- Chrf: 64.8493
## Model description
Fine-tuned for Japanese to English translation of the Ruby and Rails documentation.
## Intended uses & limitations
The training dataset (see below) is still very small, so only minor improvements are expected.
## Training and evaluation data
Trained on a custom dataset specifically based on Ruby and Ruby on Rails documentation: https://huggingface.co/datasets/morinoko-inari/ruby-rails-ja-en
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log | 1.0 | 23 | 1.7593 | 0.3283 | 64.8523 |
| No log | 2.0 | 46 | 1.6915 | 0.3260 | 64.6705 |
| No log | 3.0 | 69 | 1.6714 | 0.3300 | 64.8493 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1
|
mergekit-community/mergekit-dare_ties-zrurbjl | mergekit-community | 2025-04-20T14:51:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2311.03099",
"base_model:ReadyArt/Forgotten-Abomination-12B-v4.0",
"base_model:merge:ReadyArt/Forgotten-Abomination-12B-v4.0",
"base_model:dreamgen/lucid-v1-nemo",
"base_model:merge:dreamgen/lucid-v1-nemo",
"base_model:ftamas/Dark-Science-12B",
"base_model:merge:ftamas/Dark-Science-12B",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T14:46:11Z | ---
base_model:
- dreamgen/lucid-v1-nemo
- ReadyArt/Forgotten-Abomination-12B-v4.0
- ftamas/Dark-Science-12B
library_name: transformers
tags:
- mergekit
- merge
---
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [ftamas/Dark-Science-12B](https://huggingface.co/ftamas/Dark-Science-12B) as a base.
### Models Merged
The following models were included in the merge:
* [dreamgen/lucid-v1-nemo](https://huggingface.co/dreamgen/lucid-v1-nemo)
* [ReadyArt/Forgotten-Abomination-12B-v4.0](https://huggingface.co/ReadyArt/Forgotten-Abomination-12B-v4.0)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model: ftamas/Dark-Science-12B
merge_method: dare_ties
models:
- model: ReadyArt/Forgotten-Abomination-12B-v4.0
parameters:
weight: 0.5
- model: dreamgen/lucid-v1-nemo
parameters:
weight: 0.5
parameters:
density: 0.67
normalize: true
tokenizer_source: union
dtype: bfloat16
```
|
dgambettaphd/M_llm3_gen3_run0_WXS_doc1000_synt64_SYNLAST | dgambettaphd | 2025-04-20T14:51:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T14:51:02Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
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## Model Card Contact
[More Information Needed] |
Hartunka/bert_base_rand_20_v1_mnli | Hartunka | 2025-04-20T14:48:06Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"base_model:Hartunka/bert_base_rand_20_v1",
"base_model:finetune:Hartunka/bert_base_rand_20_v1",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-04-20T13:01:25Z | ---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_rand_20_v1_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.6673108218063466
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert_base_rand_20_v1_mnli
This model is a fine-tuned version of [Hartunka/bert_base_rand_20_v1](https://huggingface.co/Hartunka/bert_base_rand_20_v1) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7866
- Accuracy: 0.6673
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9783 | 1.0 | 1534 | 0.9197 | 0.5693 |
| 0.8746 | 2.0 | 3068 | 0.8565 | 0.6090 |
| 0.7957 | 3.0 | 4602 | 0.8150 | 0.6441 |
| 0.7173 | 4.0 | 6136 | 0.8205 | 0.6471 |
| 0.6446 | 5.0 | 7670 | 0.7996 | 0.6617 |
| 0.5725 | 6.0 | 9204 | 0.8414 | 0.6645 |
| 0.4995 | 7.0 | 10738 | 0.9119 | 0.6593 |
| 0.4289 | 8.0 | 12272 | 0.9942 | 0.6555 |
| 0.3647 | 9.0 | 13806 | 1.1232 | 0.6482 |
| 0.3083 | 10.0 | 15340 | 1.1382 | 0.6507 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
|
mergekit-community/mergekit-slerp-yhzbzvv | mergekit-community | 2025-04-20T14:46:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:mergekit-community/mergekit-slerp-mjfukvb",
"base_model:merge:mergekit-community/mergekit-slerp-mjfukvb",
"base_model:mergekit-community/mergekit-slerp-znbfpqv",
"base_model:merge:mergekit-community/mergekit-slerp-znbfpqv",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T14:32:10Z | ---
base_model:
- mergekit-community/mergekit-slerp-mjfukvb
- mergekit-community/mergekit-slerp-znbfpqv
library_name: transformers
tags:
- mergekit
- merge
---
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
### Models Merged
The following models were included in the merge:
* [mergekit-community/mergekit-slerp-mjfukvb](https://huggingface.co/mergekit-community/mergekit-slerp-mjfukvb)
* [mergekit-community/mergekit-slerp-znbfpqv](https://huggingface.co/mergekit-community/mergekit-slerp-znbfpqv)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: mergekit-community/mergekit-slerp-mjfukvb
- model: mergekit-community/mergekit-slerp-znbfpqv
merge_method: slerp
base_model: mergekit-community/mergekit-slerp-mjfukvb
tokenizer_source: mergekit-community/MN-Hekate-Damnomeneia-17B
dtype: bfloat16
parameters:
t: [0.1, 0.2, 0.4, 0.8, 0.4, 0.2, 0.1]
```
|
jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF | jasjoiefs | 2025-04-20T14:44:21Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"gemma3",
"analytical-tasks",
"bias-neutralization",
"uncensored",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"dataset:TheDrummer/AmoralQA-v2",
"base_model:soob3123/amoral-gemma3-27B-v2-qat",
"base_model:quantized:soob3123/amoral-gemma3-27B-v2-qat",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-04-20T14:43:08Z | ---
base_model: soob3123/amoral-gemma3-27B-v2-qat
datasets:
- TheDrummer/AmoralQA-v2
language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- text-generation-inference
- transformers
- gemma3
- analytical-tasks
- bias-neutralization
- uncensored
- llama-cpp
- gguf-my-repo
---
# jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF
This model was converted to GGUF format from [`soob3123/amoral-gemma3-27B-v2-qat`](https://huggingface.co/soob3123/amoral-gemma3-27B-v2-qat) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/soob3123/amoral-gemma3-27B-v2-qat) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF --hf-file amoral-gemma3-27b-v2-qat-q4_k_s.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF --hf-file amoral-gemma3-27b-v2-qat-q4_k_s.gguf -c 2048
```
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF --hf-file amoral-gemma3-27b-v2-qat-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo jasjoiefs/amoral-gemma3-27B-v2-qat-Q4_K_S-GGUF --hf-file amoral-gemma3-27b-v2-qat-q4_k_s.gguf -c 2048
```
|
HussienAhmad/FinalGoalToSkillLLaMa | HussienAhmad | 2025-04-20T14:41:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"sft",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text-generation | 2025-04-19T22:03:39Z | ---
library_name: transformers
tags:
- trl
- sft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
moyixiao/llama3_full_g | moyixiao | 2025-04-20T14:38:31Z | 8 | 0 | null | [
"tensorboard",
"safetensors",
"llama",
"region:us"
] | null | 2025-04-18T09:03:14Z |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training results
### Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
|
AdamStolcz/Aurora | AdamStolcz | 2025-04-20T14:26:45Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-04-16T20:57:35Z | ---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
# widget:
# - text: >-
# prompt
# output:
# url: https://...
instance_prompt: Aurora
---
# Aurora
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `Aurora` to trigger the image generation.
## Run this LoRA with an API using Replicate
```py
import replicate
input = {
"prompt": "Aurora",
"lora_weights": "https://huggingface.co/AdamStolcz/Aurora/resolve/main/lora.safetensors"
}
output = replicate.run(
"black-forest-labs/flux-dev-lora",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.webp", "wb") as file:
file.write(item.read())
```
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('AdamStolcz/Aurora', weight_name='lora.safetensors')
image = pipeline('Aurora').images[0]
```
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
## Training details
- Steps: 2000
- Learning rate: 0.0004
- LoRA rank: 16
## Contribute your own examples
You can use the [community tab](https://huggingface.co/AdamStolcz/Aurora/discussions) to add images that show off what you’ve made with this LoRA.
|
Naturion/SandBot_3.2 | Naturion | 2025-04-20T14:24:16Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"llama",
"text-generation-inference",
"unsloth",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T14:23:16Z | ---
base_model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- gguf
license: apache-2.0
language:
- en
---
# Uploaded model
- **Developed by:** Naturion
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
themukherjee/nonte-bengali-comic-character | themukherjee | 2025-04-20T14:20:08Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:20:08Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
risolmayo/fa8b544e-98f9-4084-9ead-9754fa250570 | risolmayo | 2025-04-20T14:17:59Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:17:50Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
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tomer-tsrouya/santa-aliana | tomer-tsrouya | 2025-04-20T14:17:20Z | 0 | 0 | null | [
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bocilanomali/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-fast_sturdy_monkey | bocilanomali | 2025-04-20T14:16:56Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am fast sturdy monkey",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-15T18:59:29Z | <!DOCTYPE html>
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NeoBoy/wav2vec2-base-timit-demo-google-colab | NeoBoy | 2025-04-20T14:16:43Z | 0 | 0 | null | [
"region:us"
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OhaymakingO/8-heytisNewA-11-20041533 | OhaymakingO | 2025-04-20T14:16:04Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
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Shannonjunior/1907d9e0-183d-47db-be05-efebc7cea113 | Shannonjunior | 2025-04-20T14:15:44Z | 0 | 0 | null | [
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DevQuasar/twinkle-ai.Llama-3.2-3B-F1-Instruct-GGUF | DevQuasar | 2025-04-20T14:13:48Z | 0 | 0 | null | [
"gguf",
"text-generation",
"base_model:twinkle-ai/Llama-3.2-3B-F1-Instruct",
"base_model:quantized:twinkle-ai/Llama-3.2-3B-F1-Instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-04-20T13:48:24Z | <!DOCTYPE html>
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<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
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Noto Color Emoji;
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width: 6rem;
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margin: 0 auto 1rem;
}
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font-size: 3.75rem;
line-height: 1;
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p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
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lesso14/aa8920cd-b092-488e-be76-7487f781027b | lesso14 | 2025-04-20T14:11:15Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:11:10Z | <!DOCTYPE html>
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mradermacher/Golden-Curry-12B-i1-GGUF | mradermacher | 2025-04-20T14:10:41Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"dataset:Mielikki/Erebus-87k",
"dataset:PocketDoc/Dans-MemoryCore-CoreCurriculum-Small",
"dataset:NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered",
"dataset:Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned",
"dataset:NewEden/Gryphe-Sonnet-3.5-35k-Subset",
"dataset:Nitral-AI/GU_Instruct-ShareGPT",
"dataset:Nitral-AI/Medical_Instruct-ShareGPT",
"dataset:AquaV/Resistance-Sharegpt",
"dataset:AquaV/US-Army-Survival-Sharegpt",
"dataset:Gryphe/Sonnet3.5-SlimOrcaDedupCleaned",
"dataset:Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned",
"dataset:ResplendentAI/bluemoon",
"dataset:hardlyworking/openerotica-freedomrp-sharegpt-system",
"dataset:MinervaAI/Aesir-Preview",
"dataset:anthracite-core/c2_logs_32k_v1.1",
"dataset:Nitral-AI/Creative_Writing-ShareGPT",
"dataset:PJMixers/lodrick-the-lafted_OpusStories-Story2Prompt-ShareGPT",
"dataset:NewEden/Opus-accepted-hermes-rejected-shuffled",
"base_model:GreenerPastures/Golden-Curry-12B",
"base_model:quantized:GreenerPastures/Golden-Curry-12B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-04-20T12:10:07Z | <!DOCTYPE html>
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lesso02/3ea6fa0b-7903-4df2-9c94-46e6089c3a97 | lesso02 | 2025-04-20T14:10:29Z | 0 | 0 | null | [
"region:us"
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HoangKhoi/Llama-3.2-3B-Instruct_LORA_1d | HoangKhoi | 2025-04-20T14:10:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T14:08:45Z | <!DOCTYPE html>
<html class="" lang="en">
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font-size: 3.75rem;
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abdulrahan8286/abrah | abdulrahan8286 | 2025-04-20T14:10:11Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2025-04-20T14:10:11Z | <!DOCTYPE html>
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}
</style>
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BlcaCola/YI-AI-Chinese-4B-it-V1-GGUF | BlcaCola | 2025-04-20T14:10:00Z | 0 | 0 | null | [
"gguf",
"image-text-to-text",
"arxiv:1910.09700",
"base_model:BlcaCola/YI-AI-Chinese-4B-it-V1",
"base_model:quantized:BlcaCola/YI-AI-Chinese-4B-it-V1",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-04-19T14:31:41Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
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/>
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/>
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Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
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font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
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testrightnow/393aa17e-aad3-4f79-84a7-fe59eed4f3b6 | testrightnow | 2025-04-20T14:09:40Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:09:18Z | <!DOCTYPE html>
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Noto Color Emoji;
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width: 6rem;
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}
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sergioalves/f45b4a99-4582-4287-a115-13cd735636cb | sergioalves | 2025-04-20T14:09:21Z | 0 | 0 | peft | [
"peft",
"safetensors",
"phi3",
"axolotl",
"generated_from_trainer",
"custom_code",
"base_model:microsoft/Phi-3-mini-4k-instruct",
"base_model:adapter:microsoft/Phi-3-mini-4k-instruct",
"license:mit",
"region:us"
] | null | 2025-04-20T13:01:10Z | <!DOCTYPE html>
<html class="" lang="en">
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<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
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ppx007/ThisIsTMP | ppx007 | 2025-04-20T14:08:57Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:unsloth/gemma-2-9b-bnb-4bit",
"base_model:adapter:unsloth/gemma-2-9b-bnb-4bit",
"region:us"
] | null | 2025-04-20T11:06:15Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
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img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
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color: rgba(107, 114, 128, 1);
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line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
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.dark h1 {
color: rgb(209, 213, 219);
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.dark p, .dark a {
color: rgb(156, 163, 175);
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<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
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Eehan/Pythia-1b-deduped-tldr-drpo | Eehan | 2025-04-20T14:08:09Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:08:07Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
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img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
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color: rgba(107, 114, 128, 1);
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line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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nqzfaizal77ai/sa-145m-en-1bc-space-warfare-short-story-3pov-exp-intro | nqzfaizal77ai | 2025-04-20T14:06:38Z | 0 | 0 | null | [
"safetensors",
"falcon",
"custom_code",
"region:us"
] | null | 2025-04-20T14:06:11Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
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h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
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box-sizing: border-box;
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line-height: 1.75rem;
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box-sizing: border-box;
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color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
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: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
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MaryemOuichka/mistral_complet | MaryemOuichka | 2025-04-20T14:05:01Z | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:mistralai/Mistral-7B-Instruct-v0.1",
"base_model:adapter:mistralai/Mistral-7B-Instruct-v0.1",
"region:us"
] | null | 2025-04-20T14:04:59Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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/>
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body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
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img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
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line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
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}
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color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
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}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
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<img
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alt=""
/>
<div>
<h1>429</h1>
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li55555/zephyr_v2.1_iter1 | li55555 | 2025-04-20T14:04:04Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T14:04:04Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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<style>
body {
margin: 0;
}
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background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
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}
</script>
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<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
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nhatminh/money-0.2 | nhatminh | 2025-04-20T14:03:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T13:59:16Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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/>
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<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
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} catch (e) {}
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document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
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<img
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alt=""
/>
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<h1>429</h1>
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asdfre453/throat | asdfre453 | 2025-04-20T14:01:12Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T13:52:59Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
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/>
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content="Hugging Face - The AI community building the future."
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<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
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<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
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ArikaGrimmer/Aodio_Diffusion_Test_Models | ArikaGrimmer | 2025-04-20T13:59:34Z | 0 | 1 | null | [
"region:us"
] | null | 2025-04-20T13:32:28Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
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/>
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content="Hugging Face - The AI community building the future."
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<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
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Bouquets/StrikeGPT-R1-Zero-1.5B | Bouquets | 2025-04-20T13:58:12Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T13:58:12Z | <!DOCTYPE html>
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img {
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}
h1 {
font-size: 3.75rem;
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color: rgba(31, 41, 55, 1);
font-weight: 700;
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p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
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max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
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.dark p, .dark a {
color: rgb(156, 163, 175);
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jamshaid2384411/bitcoinminer | jamshaid2384411 | 2025-04-20T13:57:47Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2025-04-20T13:57:47Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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}
img {
width: 6rem;
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margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
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font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
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p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
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Axile741/1b098c9b-72cc-4742-a0c9-ec90f654c3f4 | Axile741 | 2025-04-20T13:55:01Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T13:54:53Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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margin: 0;
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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<img
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alt=""
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<div>
<h1>429</h1>
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DreadPoor/Still | DreadPoor | 2025-04-20T13:54:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2403.19522",
"base_model:DreadPoor/Irix-12B-Model_Stock",
"base_model:merge:DreadPoor/Irix-12B-Model_Stock",
"base_model:DreadPoor/YM-12B-Model_Stock",
"base_model:merge:DreadPoor/YM-12B-Model_Stock",
"base_model:yamatazen/Aurora-SCE-12B",
"base_model:merge:yamatazen/Aurora-SCE-12B",
"base_model:yamatazen/Ayla-Light-12B-Stock",
"base_model:merge:yamatazen/Ayla-Light-12B-Stock",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T13:49:20Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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content="Hugging Face - The AI community building the future."
/>
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<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
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<img
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alt=""
/>
<div>
<h1>429</h1>
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SKNahin/BQTrans-3-2 | SKNahin | 2025-04-20T13:54:39Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-04-20T12:06:20Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
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<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
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<body>
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<img
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alt=""
/>
<div>
<h1>429</h1>
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vmpsergio/dccbf031-ba5b-4ecc-82e9-e983bd60685b | vmpsergio | 2025-04-20T13:50:56Z | 0 | 0 | peft | [
"peft",
"safetensors",
"phi3",
"axolotl",
"generated_from_trainer",
"custom_code",
"base_model:microsoft/Phi-3-mini-4k-instruct",
"base_model:adapter:microsoft/Phi-3-mini-4k-instruct",
"license:mit",
"region:us"
] | null | 2025-04-20T12:44:06Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
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<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
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RichardErkhov/klcsp_-_mistral7b-fft-coding-11-v1-gguf | RichardErkhov | 2025-04-20T13:50:26Z | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T11:39:11Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
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<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
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</body>
</html> |
prl90777/deepseek_r1_qwen_14_20250418_0 | prl90777 | 2025-04-20T13:49:00Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2025-04-19T03:44:39Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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<meta
property="og:title"
content="Hugging Face - The AI community building the future."
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
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Fidan56/detr_fashion_ckpt | Fidan56 | 2025-04-20T13:48:19Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"base_model:facebook/detr-resnet-50",
"base_model:finetune:facebook/detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | object-detection | 2025-04-20T13:48:06Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
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/>
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content="Hugging Face - The AI community building the future."
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}
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
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theme = storageTheme === "dark" ? "dark" : "light";
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alt=""
/>
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<h1>429</h1>
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OriginalMehrdad/ppo-Huggy | OriginalMehrdad | 2025-04-20T13:46:11Z | 0 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | reinforcement-learning | 2025-04-20T13:46:04Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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property="og:title"
content="Hugging Face - The AI community building the future."
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<style>
body {
margin: 0;
}
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padding: 7rem 1rem 8rem 1rem;
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font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
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} catch (e) {}
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alt=""
/>
<div>
<h1>429</h1>
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tarabukinivan/mydata | tarabukinivan | 2025-04-20T13:43:04Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-10T23:05:55Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
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<meta
property="og:title"
content="Hugging Face - The AI community building the future."
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<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
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<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
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DevQuasar/google.gemma-3-27b-it-qat-q4_0-unquantized-GGUF | DevQuasar | 2025-04-20T13:42:44Z | 0 | 0 | null | [
"gguf",
"image-text-to-text",
"base_model:google/gemma-3-27b-it-qat-q4_0-unquantized",
"base_model:quantized:google/gemma-3-27b-it-qat-q4_0-unquantized",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-04-20T05:37:26Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
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</script>
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<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
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adamleaked/adam-benchekroun-telegram | adamleaked | 2025-04-20T13:42:20Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T13:41:13Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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document.documentElement.classList.add("dark");
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document.documentElement.classList.remove("dark");
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<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
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maithicamlinh1983/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-slithering_smooth_okapi | maithicamlinh1983 | 2025-04-20T13:41:03Z | 6 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am slithering smooth okapi",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-17T12:24:18Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
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document.documentElement.classList.remove("dark");
}
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<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
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</body>
</html> |
sanjibani/wav2vec2-kui1 | sanjibani | 2025-04-20T13:33:58Z | 0 | 0 | null | [
"safetensors",
"wav2vec2",
"region:us"
] | null | 2025-04-20T08:12:01Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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axolotlman42/63e205c5-8e17-40dd-bdcc-ebd4e11133f6 | axolotlman42 | 2025-04-20T13:32:39Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-04-20T12:31:43Z | <!DOCTYPE html>
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.dark main {
background-color: rgb(11, 15, 25);
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Kuvshin/models | Kuvshin | 2025-04-20T13:28:31Z | 0 | 1 | null | [
"region:us"
] | null | 2024-01-25T11:03:55Z | <!DOCTYPE html>
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}
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font-size: 3.75rem;
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color: rgba(107, 114, 128, 1);
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.dark main {
background-color: rgb(11, 15, 25);
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RichardErkhov/mlfoundations-dev_-_oh-mistral-bs1024_lr2_00E-06_schedulerconstant_warmup1_00E-01_minlr-gguf | RichardErkhov | 2025-04-20T13:25:36Z | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T11:06:05Z | <!DOCTYPE html>
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<head>
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Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
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p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
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? "dark"
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if (storageTheme) {
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croixsanct/aifufufafa | croixsanct | 2025-04-20T13:23:30Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2025-04-20T13:23:30Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
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aniket-meta/llama-3.1-8b-mkb-lora-target-v3 | aniket-meta | 2025-04-20T13:20:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T13:17:11Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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/>
<meta property="fb:app_id" content="1321688464574422" />
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/>
<meta property="og:type" content="website" />
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<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
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if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
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alt=""
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nkkbr/ViCA-ARKitScenes-90p | nkkbr | 2025-04-20T13:18:03Z | 0 | 0 | null | [
"safetensors",
"llava",
"region:us"
] | null | 2025-04-20T11:02:23Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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/>
<meta property="fb:app_id" content="1321688464574422" />
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<meta name="twitter:site" content="@huggingface" />
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content="Hugging Face - The AI community building the future."
/>
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<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
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background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
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alt=""
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ashwin010293/ppo-Huggy | ashwin010293 | 2025-04-20T13:16:41Z | 0 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | reinforcement-learning | 2025-04-20T13:16:34Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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margin: 0;
}
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min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
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const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
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document.documentElement.classList.add("dark");
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<img
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alt=""
/>
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JakeMilne/DenseNet169 | JakeMilne | 2025-04-20T13:12:54Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2025-04-20T13:12:08Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
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<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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}
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min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
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chaymaa2004/vitalisMultiple | chaymaa2004 | 2025-04-20T13:11:21Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"llama",
"text-generation-inference",
"unsloth",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T13:09:01Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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img {
width: 6rem;
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background-color: rgb(11, 15, 25);
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mohhtl/test_flux | mohhtl | 2025-04-20T13:08:15Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T13:08:12Z | <!DOCTYPE html>
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<script>
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dieppham197011/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-foxy_unseen_coyote | dieppham197011 | 2025-04-20T13:07:07Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"rl-swarm",
"grpo",
"gensyn",
"I am foxy unseen coyote",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Gensyn/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Gensyn/Qwen2.5-0.5B-Instruct",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-18T11:40:38Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
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color: rgb(156, 163, 175);
}
</style>
<script>
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if (storageTheme) {
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ghaniashafiqa/FT-Qwen2.5-3b-Adapter-2 | ghaniashafiqa | 2025-04-20T13:05:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T13:05:06Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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/>
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Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
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font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
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background-color: rgb(11, 15, 25);
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}
.dark p, .dark a {
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}
</style>
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ma921/pythia-70m_c_dpo_hh | ma921 | 2025-04-20T13:04:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:ma921/pythia-70m_sft_hh",
"base_model:finetune:ma921/pythia-70m_sft_hh",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T13:03:53Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
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content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
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</style>
<script>
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let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
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theme = storageTheme === "dark" ? "dark" : "light";
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sergioalves/846b78c2-88c5-436e-b28a-299ef64b807f | sergioalves | 2025-04-20T13:00:00Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama",
"axolotl",
"generated_from_trainer",
"base_model:unsloth/tinyllama",
"base_model:adapter:unsloth/tinyllama",
"license:apache-2.0",
"region:us"
] | null | 2025-04-20T12:42:27Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
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/>
<meta property="fb:app_id" content="1321688464574422" />
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<meta
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
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font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
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color: rgb(209, 213, 219);
}
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color: rgb(156, 163, 175);
}
</style>
<script>
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Hartunka/bert_base_rand_20_v1_sst2 | Hartunka | 2025-04-20T12:58:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"base_model:Hartunka/bert_base_rand_20_v1",
"base_model:finetune:Hartunka/bert_base_rand_20_v1",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-04-20T12:46:36Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
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alt=""
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Rouven123/QA-GPT2 | Rouven123 | 2025-04-20T12:52:58Z | 0 | 0 | null | [
"tensorboard",
"safetensors",
"gpt2",
"region:us"
] | null | 2025-04-20T11:44:49Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
fedovtt/d81a0a4f-8f38-41df-ac85-c2adf7761b36 | fedovtt | 2025-04-20T12:52:14Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"axolotl",
"generated_from_trainer",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-3B-Instruct",
"license:other",
"8-bit",
"bitsandbytes",
"region:us"
] | null | 2025-04-20T12:26:20Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
sachi03122/pm | sachi03122 | 2025-04-20T12:51:57Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:40:30Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
goodenwings/813dab7d-29f7-4f68-9199-040a8f4c4d0f | goodenwings | 2025-04-20T12:51:19Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:51:15Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
kamelcharaf/GRPO-meta-Llama-3.2-1B-meta-Llama-3.2-1B-mrd3-s3-sum | kamelcharaf | 2025-04-20T12:51:04Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:51:04Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
tellmenanson/89c16465-b5fe-4e47-af0d-733892b06bed | tellmenanson | 2025-04-20T12:50:41Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:50:34Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
error577/520e9f77-90c5-43a2-af81-c4fd2460899b | error577 | 2025-04-20T12:46:18Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T11:53:26Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
<main>
<img
src="https://cdn-media.huggingface.co/assets/huggingface_logo.svg"
alt=""
/>
<div>
<h1>429</h1>
<p>We had to rate limit you. If you think it's an error, send us <a href="mailto:[email protected]">an email</a></p>
</div>
</main>
</body>
</html> |
luckeciano/Qwen-2.5-7B-RL-AC-BigLRv3-Fast-4-v6-Train-NoKL | luckeciano | 2025-04-20T12:46:16Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:46:16Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
<meta
name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:site" content="@huggingface" />
<meta
property="og:title"
content="Hugging Face - The AI community building the future."
/>
<meta property="og:type" content="website" />
<title>Hugging Face - The AI community building the future.</title>
<style>
body {
margin: 0;
}
main {
background-color: white;
min-height: 100vh;
padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
: "light";
try {
const storageTheme = JSON.parse(window.localStorage.getItem(key)).theme;
if (storageTheme) {
theme = storageTheme === "dark" ? "dark" : "light";
}
} catch (e) {}
if (theme === "dark") {
document.documentElement.classList.add("dark");
} else {
document.documentElement.classList.remove("dark");
}
</script>
</head>
<body>
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<img
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KHAOULA-KH/CAR_DOMMAGE_BASE | KHAOULA-KH | 2025-04-20T12:46:07Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
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RichardErkhov/klcsp_-_mistral7b-fft-closedqa-11-v1-gguf | RichardErkhov | 2025-04-20T12:44:47Z | 0 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
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Steve4Alpha/5e17c65d-206d-4a08-8282-cadf4c67a31b | Steve4Alpha | 2025-04-20T12:44:36Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:44:26Z | <!DOCTYPE html>
<html class="" lang="en">
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Noto Color Emoji;
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img {
width: 6rem;
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margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
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p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
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max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
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}
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color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
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nkkbr/ViCA-ARKitScenes-40p | nkkbr | 2025-04-20T12:37:52Z | 0 | 0 | null | [
"safetensors",
"llava",
"region:us"
] | null | 2025-04-20T11:02:17Z | <!DOCTYPE html>
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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ngtranAI1/RawTrend | ngtranAI1 | 2025-04-20T12:37:42Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-04-19T10:27:31Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
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<meta
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
? "dark"
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sapadev13/SAPA_model | sapadev13 | 2025-04-20T12:34:04Z | 189 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"feature-extraction",
"arxiv:1910.09700",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2025-04-03T07:45:12Z | <!DOCTYPE html>
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
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aksrmy/EfficientNetB1Xray | aksrmy | 2025-04-20T12:33:56Z | 0 | 0 | keras | [
"keras",
"license:apache-2.0",
"region:us"
] | null | 2025-04-20T12:33:39Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
// On page load or when changing themes, best to add inline in `head` to avoid FOUC
const key = "_tb_global_settings";
let theme = window.matchMedia("(prefers-color-scheme: dark)").matches
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if (storageTheme) {
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OhaymakingO/5-heytisNewA-11-20041353 | OhaymakingO | 2025-04-20T12:33:52Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-04-20T10:58:09Z | <!DOCTYPE html>
<html class="" lang="en">
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content="width=device-width, initial-scale=1.0, user-scalable=no"
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margin: 0;
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background-color: white;
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text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
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freemanjiang/foldshirt | freemanjiang | 2025-04-20T12:33:12Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2025-04-20T11:29:05Z | <!DOCTYPE html>
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biaofu-xmu/wav2vec-S-Base | biaofu-xmu | 2025-04-20T12:32:44Z | 3 | 0 | null | [
"safetensors",
"wav2vec2",
"en",
"license:apache-2.0",
"region:us"
] | null | 2025-04-15T20:29:00Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
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}
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mradermacher/proposly-tinyllama-GGUF | mradermacher | 2025-04-20T12:31:45Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Gandhiv112/proposly-tinyllama",
"base_model:quantized:Gandhiv112/proposly-tinyllama",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T12:20:34Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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margin: 0;
}
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padding: 7rem 1rem 8rem 1rem;
text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
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}
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</style>
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RocketRaccoonnn/CodeLlama-13b-Instruct-hf_PROMPT_TUNING_CAUSAL_LM_v1_1 | RocketRaccoonnn | 2025-04-20T12:30:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T12:29:58Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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}
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BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
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ursolaqua/753fade2-e70d-4afd-9b39-88f5c190d440 | ursolaqua | 2025-04-20T12:29:49Z | 0 | 0 | null | [
"region:us"
] | null | 2025-04-20T12:02:24Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
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}
.dark p, .dark a {
color: rgb(156, 163, 175);
}
</style>
<script>
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moonshotai/Kimi-VL-A3B-Instruct | moonshotai | 2025-04-20T12:28:03Z | 22,627 | 177 | transformers | [
"transformers",
"safetensors",
"kimi_vl",
"feature-extraction",
"agent",
"video",
"screenspot",
"long-context",
"image-text-to-text",
"conversational",
"custom_code",
"arxiv:2504.07491",
"base_model:moonshotai/Moonlight-16B-A3B",
"base_model:finetune:moonshotai/Moonlight-16B-A3B",
"license:mit",
"region:us"
] | image-text-to-text | 2025-04-09T08:07:06Z | <!DOCTYPE html>
<html class="" lang="en">
<head>
<meta charset="utf-8" />
<meta
name="viewport"
content="width=device-width, initial-scale=1.0, user-scalable=no"
/>
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name="description"
content="We're on a journey to advance and democratize artificial intelligence through open source and open science."
/>
<meta property="fb:app_id" content="1321688464574422" />
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margin: 0;
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background-color: white;
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text-align: center;
font-family: Source Sans Pro, ui-sans-serif, system-ui, -apple-system,
BlinkMacSystemFont, Segoe UI, Roboto, Helvetica Neue, Arial, Noto Sans,
sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol,
Noto Color Emoji;
}
img {
width: 6rem;
height: 6rem;
margin: 0 auto 1rem;
}
h1 {
font-size: 3.75rem;
line-height: 1;
color: rgba(31, 41, 55, 1);
font-weight: 700;
box-sizing: border-box;
margin: 0 auto;
}
p, a {
color: rgba(107, 114, 128, 1);
font-size: 1.125rem;
line-height: 1.75rem;
max-width: 28rem;
box-sizing: border-box;
margin: 0 auto;
}
.dark main {
background-color: rgb(11, 15, 25);
}
.dark h1 {
color: rgb(209, 213, 219);
}
.dark p, .dark a {
color: rgb(156, 163, 175);
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mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF | mradermacher | 2025-04-20T12:25:48Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"trl",
"en",
"dataset:UCSC-VLAA/STAR-1",
"base_model:EpistemeAI/SADeepCoder-1.5B-Preview-v1",
"base_model:quantized:EpistemeAI/SADeepCoder-1.5B-Preview-v1",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-04-20T11:27:51Z | ---
base_model: EpistemeAI/SADeepCoder-1.5B-Preview-v1
datasets:
- UCSC-VLAA/STAR-1
language:
- en
library_name: transformers
license: mit
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/EpistemeAI/SADeepCoder-1.5B-Preview-v1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q2_K.gguf) | Q2_K | 0.9 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q3_K_S.gguf) | Q3_K_S | 1.0 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q3_K_M.gguf) | Q3_K_M | 1.0 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q3_K_L.gguf) | Q3_K_L | 1.1 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.IQ4_XS.gguf) | IQ4_XS | 1.1 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q4_K_S.gguf) | Q4_K_S | 1.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q4_K_M.gguf) | Q4_K_M | 1.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q5_K_S.gguf) | Q5_K_S | 1.4 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q5_K_M.gguf) | Q5_K_M | 1.4 | |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q6_K.gguf) | Q6_K | 1.6 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.Q8_0.gguf) | Q8_0 | 2.0 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/SADeepCoder-1.5B-Preview-v1-GGUF/resolve/main/SADeepCoder-1.5B-Preview-v1.f16.gguf) | f16 | 3.7 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->
|
cvillejustin/mistral_custom_lora | cvillejustin | 2025-04-20T12:23:17Z | 11 | 0 | peft | [
"peft",
"safetensors",
"base_model:mistralai/Mistral-7B-Instruct-v0.1",
"base_model:adapter:mistralai/Mistral-7B-Instruct-v0.1",
"region:us"
] | null | 2025-04-17T01:23:59Z | ---
base_model: mistralai/Mistral-7B-Instruct-v0.1
library_name: peft
---
### Introduction
This model was fine-tuned to extract scientific equipment details from the methods sections of academic articles. The goal is to generate structured JSON outputs capturing the name, model, brand, and country of origin (if available) of research equipment. This task is important because existing metadata sources like Web of Science or PubMed often lack consistent or complete information about research infrastructure. Understanding what tools are used in emerging scientific domains can support both academic analysis and strategic insights for industry. While general-purpose LLMs can parse text well, they struggle with producing structured, domain-specific outputs. Fine-tuning was necessary to teach the model how to identify and organize equipment details reliably. The resulting model shows strong performance on extracting relevant information and provides a valuable foundation for downstream research infrastructure analysis.
### Training Data
The training dataset was constructed from a custom corpus of academic articles drawn from bioRxiv.org, the preprint server for biology, which hosts open-access scientific articles. For each article, the methods section was extracted and paired with structured annotations specifying the scientific equipment mentioned, including fields for name, brand, model, and country of origin when available. These annotations were generated using a few-shot prompting strategy with OpenAI’s GPT-4o mini model and then manually reviewed for quality. The data was formatted into JSONL with instruction-following input/output fields suitable for supervised fine-tuning. A fixed random seed of 42 was used for reproducibility during the test-train split. The dataset did not come with a built-in test set, so this split was created manually from the full annotated corpus.
### Training Method
We fine-tuned the Mistral-7B-Instruct-v0.1 model using the HuggingFace transformers library with parameter-efficient fine-tuning via LoRA. We chose this method to reduce computational cost while still allowing the model to specialize in structured extraction tasks. The model was trained to generate JSON-style outputs containing equipment details (name, brand, model, country of origin) from the methods sections of academic articles. We used a learning rate of 2e-5, batch size of 4, and trained for 3 epochs with early stopping based on validation loss. Our fine-tuning setup used the AdamW optimizer with a warmup ratio of 0.1 and a linear learning rate scheduler. These hyperparameters were chosen after initial experiments balancing performance and training efficiency.
### Evaluation
To evaluate the effectiveness of the fine-tuned model on scientific equipment extraction, I tested performance across three benchmark tasks: WikiANN and CoNLL-2003 (named entity recognition datasets), as well as my own custom dataset of scientific method sections manually annotated for equipment mentions. I also used a test set to generate metrics for comparison.
The CoNLL-2003 and WikiANN datasets served as standard NER benchmarks to measure general extraction ability, while my manually tagged dataset and custom test set focused on domain-specific extraction of scientific equipment from academic articles. I selected Zephyr-7B and OpenChat-3.5 as comparison models because they are similar in size to my Mistral-7B base model and represent open-source instruction-tuned alternatives that are commonly used in applied NLP. Compared to these models, my post-PEFT fine-tuned Mistral significantly outperformed both on all four benchmarks, especially on the domain-specific tasks, where it achieved more than 5× the F1 score of Zephyr and nearly doubled the performance of OpenChat.
**F1 Score Comparison Across Benchmarks**
| Benchmark | Mistral (pre) | Mistral (post) | Zephyr-7B | OpenChat-3.5 |
|--------------------------|---------------|----------------|------------|---------------|
| **CoNLL-2003** | 0.167 | 0.257 | 0.119 | 0.120 |
| **Manual Tagged** | 0.073 | 0.525 | 0.036 | 0.260 |
| **WikiANN** | 0.111 | 0.154 | 0.010 | 0.029 |
| **Equipment Test Set** | 0.222 | 0.539 | 0.074 | 0.434 |
**Precision Comparison Across Benchmarks**
| Benchmark | Mistral (pre) | Mistral (post) | Zephyr-7B | OpenChat-3.5 |
|--------------------------|---------------|----------------|------------|---------------|
| **CoNLL-2003** | 0.136 | 0.221 | 0.134 | 0.199 |
| **Manual Tagged** | 0.074 | 0.452 | 0.061 | 0.304 |
| **WikiANN** | 0.132 | 0.182 | 0.009 | 0.036 |
| **Equipment Test Set** | 0.219 | 0.501 | 0.082 | 0.478 |
**Recall Comparison Across Benchmarks**
| Benchmark | Mistral (pre) | Mistral (post) | Zephyr-7B | OpenChat-3.5 |
|--------------------------|---------------|----------------|------------|---------------|
| **CoNLL-2003** | 0.214 | 0.307 | 0.107 | 0.086 |
| **Manual Tagged** | 0.072 | 0.627 | 0.025 | 0.227 |
| **WikiANN** | 0.096 | 0.133 | 0.011 | 0.024 |
| **Equipment Test Set** | 0.226 | 0.584 | 0.068 | 0.397 |
I compared my model to the base Mistral-7B model (used without finetuning) and observed substantial improvements across all evaluation settings. Notably, my model improved F1 score on my custom test set from 0.222 to 0.539, and improved manual tagging F1 from 0.073 to 0.725. Even on general-purpose NER tasks like CoNLL-2003 and WikiANN, performance improved meaningfully, suggesting that my instruction tuning led to more generalizable entity extraction behavior.
### Usage and Intended Uses
This model was fine-tuned to extract structured information about scientific supplies and equipment from the methods sections of academic articles. It is designed for use cases that require converting unstructured text into structured JSON, such as research metadata pipelines, equipment indexing, or automated review support. While optimized for biomedical research articles, the model may generalize to similar domains that use technical descriptions of laboratory processes and materials.
```{python}\n
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_name = "cvillejustin/mistral_custom_lora"
# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_name)
# Load the model using efficient memory settings
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype=torch.float16,
device_map="auto",
low_cpu_mem_usage=True
)
# Example inference
prompt = (
"[INST] Extract structured information about supplies and equipment used in the scientific article. "
"Return ONLY valid JSON—no explanations, extra text, or reformatting. "
"Extract only equipment and materials mentioned in the text. "
"If any field (brand, model, or country of origin) is missing, mark it as 'Unknown'. "
"If no equipment is found, return: { \"equipment_list\": [] }. "
"Do not repeat the article text in the response. "
"Do not add explanations, opinions, or anything outside the JSON format. "
"\n\nMice were housed in polycarbonate cages (Tecniplast) and fed with standard chow (Envigo 2018S). Cells were sorted using a FACSAria III (BD Biosciences). [/INST]"
)
# Tokenize and generate
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(**inputs, max_new_tokens=256)
# Decode response
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```
### Prompt Format
This model expects input in a simple instruction format that clearly specifies the task. Prompts begin with an [INST] tag, followed by the instruction and the target content.
```{python}\n
[INST] Extract structured information about supplies and equipment used in the scientific article.
Return ONLY valid JSON—no explanations, extra text, or reformatting.
Extract only equipment and materials mentioned in the text.
If any field (brand, model, or country of origin) is missing, mark it as 'Unknown'.
If no equipment is found, return: { "equipment_list": [] }.
C57BL/6J mice (8–18-week-old male) were purchased from Orient Bio. Jurkat T cells (Clone E6-1, ATCC) and RPMI media (Gibco) were used... [/INST]
```
### Expected Output Format
The model returns a JSON object containing an equipment_list field. This field holds a list of dictionaries, each representing a detected piece of equipment with fields for name, brand, model, and country_of_origin. Missing information is labeled as "Unknown".
```{python}\n
{
"equipment_list": [
{
"name": "RPMI media",
"brand": "Gibco",
"model": "Unknown",
"country_of_origin": "Unknown"
},
{
"name": "Jurkat T cells",
"brand": "ATCC",
"model": "Clone E6-1",
"country_of_origin": "Unknown"
}
]
}
```
### Limitations
While the model performs well on structured extraction of equipment from scientific texts, it has several limitations. First, its accuracy is dependent on the clarity and specificity of the language in the article. Ambiguous or highly technical phrasing can reduce extraction quality. Second, the model occasionally misses equipment that is mentioned implicitly or across multiple sentences. Additionally, when brand or model details are not explicitly stated, the model may inconsistently default to “Unknown”.
### Framework versions
- PEFT 0.14.0 |
phospho-app/ball_anker-wkces6yswm | phospho-app | 2025-04-20T12:20:12Z | 0 | 0 | null | [
"safetensors",
"gr00t_n1",
"phosphobot",
"gr00t",
"replicate",
"region:us"
] | null | 2025-04-20T11:58:20Z |
---
tags:
- phosphobot
- gr00t
- replicate
task_categories:
- robotics
---
# Gr00t Model - phospho Replication Pipeline
This model was trained using **phospho's Replicate pipeline** for **gr00t models**.
Training parameters:
- **Dataset**: [pgoffin/ball_anker](https://huggingface.co/datasets/pgoffin/ball_anker)
- **Wandb run URL**: https://wandb.ai/artcomputer123-artcomputer/gr00t-replicate/runs/j3ivhkfd
- **Epochs**: 10
- **Batch size**: 64
- **Training steps**: 1026
📖 **Get Started**: [docs.phospho.ai](https://docs.phospho.ai?utm_source=replicate_groot_training_pipeline)
🤖 **Get your robot**: [robots.phospho.ai](https://robots.phospho.ai?utm_source=replicate_groot_training_pipeline)
🔗 **Explore on Replicate**: [Replicate](https://replicate.com/phospho-app/gr00t-policy)
|
GlemVNT/VNT | GlemVNT | 2025-04-20T12:20:10Z | 0 | 0 | transformers | [
"transformers",
"echuku",
"text-generation",
"vnt",
"VNT-3.5F-16K",
"aa",
"ab",
"ae",
"af",
"ak",
"am",
"an",
"ar",
"as",
"av",
"ay",
"az",
"ba",
"bg",
"be",
"bi",
"bh",
"bn",
"bm",
"bo",
"br",
"bs",
"ca",
"ce",
"ch",
"co",
"cr",
"cu",
"cv",
"cy",
"da",
"de",
"dv",
"dz",
"ee",
"el",
"en",
"eo",
"es",
"et",
"cs",
"eu",
"fa",
"ff",
"fi",
"fj",
"fo",
"fr",
"fy",
"ga",
"gl",
"gn",
"gu",
"gv",
"gd",
"ha",
"he",
"hi",
"ho",
"hr",
"ht",
"hu",
"hy",
"hz",
"ia",
"id",
"ig",
"ii",
"ik",
"io",
"is",
"ie",
"it",
"iu",
"ja",
"jv",
"ka",
"kg",
"ki",
"kj",
"kk",
"kl",
"km",
"kn",
"kr",
"ks",
"ku",
"kv",
"kw",
"ky",
"ko",
"la",
"lb",
"lg",
"li",
"ln",
"lo",
"lt",
"lu",
"lv",
"mg",
"mh",
"mi",
"mk",
"ml",
"mn",
"mr",
"ms",
"my",
"na",
"nb",
"nd",
"ne",
"ng",
"nl",
"mt",
"nn",
"no",
"nr",
"nv",
"ny",
"oc",
"oj",
"om",
"or",
"os",
"pa",
"pi",
"pl",
"ps",
"qu",
"pt",
"rm",
"rn",
"ro",
"ru",
"rw",
"sa",
"sd",
"se",
"sg",
"si",
"sk",
"sl",
"sc",
"sm",
"sn",
"sq",
"sr",
"ss",
"st",
"su",
"sv",
"sw",
"ta",
"so",
"tg",
"th",
"te",
"ti",
"tk",
"tl",
"tn",
"to",
"tr",
"ts",
"tt",
"tw",
"ty",
"ug",
"uk",
"ur",
"uz",
"ve",
"vi",
"vo",
"wa",
"wo",
"xh",
"yi",
"yo",
"zh",
"za",
"zu",
"base_model:google/gemma-2b",
"base_model:finetune:google/gemma-2b",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-04-20T10:58:28Z | ---
license: mit
language:
- aa
- ab
- ae
- af
- ak
- am
- an
- ar
- as
- av
- ay
- az
- ba
- bg
- be
- bi
- bh
- bn
- bm
- bo
- br
- bs
- ca
- ce
- ch
- co
- cr
- cu
- cv
- cy
- da
- de
- dv
- dz
- ee
- el
- en
- eo
- es
- et
- cs
- eu
- fa
- ff
- fi
- fj
- fo
- fr
- fy
- ga
- gl
- gn
- gu
- gv
- gd
- ha
- he
- hi
- ho
- hr
- ht
- hu
- hy
- hz
- ia
- id
- ig
- ii
- ik
- io
- is
- ie
- it
- iu
- ja
- jv
- ka
- kg
- ki
- kj
- kk
- kl
- km
- kn
- kr
- ks
- ku
- kv
- kw
- ky
- ko
- la
- lb
- lg
- li
- ln
- lo
- lt
- lu
- lv
- mg
- mh
- mi
- mk
- ml
- mn
- mr
- ms
- my
- na
- nb
- nd
- ne
- ng
- nl
- mt
- nn
- 'no'
- nr
- nv
- ny
- oc
- oj
- om
- or
- os
- pa
- pi
- pl
- ps
- qu
- pt
- rm
- rn
- ro
- ru
- rw
- sa
- sd
- se
- sg
- si
- sk
- sl
- sc
- sm
- sn
- sq
- sr
- ss
- st
- su
- sv
- sw
- ta
- so
- tg
- th
- te
- ti
- tk
- tl
- tn
- to
- tr
- ts
- tt
- tw
- ty
- ug
- uk
- ur
- uz
- ve
- vi
- vo
- wa
- wo
- xh
- yi
- yo
- zh
- za
- zu
base_model:
- google/gemma-2b
library_name: transformers
tags:
- echuku
- text-generation
- vnt
- VNT-3.5F-16K
--- |
mohammadmahdinouri/expressive-interleaved-1b | mohammadmahdinouri | 2025-04-20T12:19:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-04-20T12:16:34Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
#### Training Hyperparameters
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
#### Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed] |
jleem/deberta_core_technology | jleem | 2025-04-20T12:17:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"base_model:kisti/korscideberta",
"base_model:finetune:kisti/korscideberta",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-04-20T12:16:47Z | ---
library_name: transformers
license: mit
base_model: kisti/korscideberta
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta_core_technology
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta_core_technology
This model is a fine-tuned version of [kisti/korscideberta](https://huggingface.co/kisti/korscideberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6353
- Accuracy: 0.7619
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3704 | 16.6667 | 100 | 0.8123 | 0.7143 |
| 0.1265 | 33.3333 | 200 | 1.0535 | 0.7619 |
| 0.0101 | 50.0 | 300 | 3.6353 | 0.7619 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
|
rocker417/xlm-roberta-toxicity-regression-ptp-all-languages-3 | rocker417 | 2025-04-20T12:16:13Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-04-20T07:42:50Z | ---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-toxicity-regression-ptp-all-languages-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-toxicity-regression-ptp-all-languages-3
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0149
- Mse: 0.0149
- Mae: 0.0914
- R2: 0.8297
- Arabic Mse: 0.0165
- Arabic Mae: 0.0951
- Arabic R2: 0.8225
- Chinese Mse: 0.0187
- Chinese Mae: 0.1023
- Chinese R2: 0.7755
- Czech Mse: 0.0130
- Czech Mae: 0.0844
- Czech R2: 0.8506
- Dutch Mse: 0.0155
- Dutch Mae: 0.0924
- Dutch R2: 0.8184
- English Mse: 0.0109
- English Mae: 0.0775
- English R2: 0.8847
- French Mse: 0.0130
- French Mae: 0.0870
- French R2: 0.8532
- German Mse: 0.0205
- German Mae: 0.1102
- German R2: 0.7295
- Hindi Mse: 0.0138
- Hindi Mae: 0.0884
- Hindi R2: 0.8389
- Indonesian Mse: 0.0112
- Indonesian Mae: 0.0815
- Indonesian R2: 0.8750
- Italian Mse: 0.0104
- Italian Mae: 0.0789
- Italian R2: 0.8796
- Japanese Mse: 0.0168
- Japanese Mae: 0.0934
- Japanese R2: 0.8177
- Korean Mse: 0.0138
- Korean Mae: 0.0900
- Korean R2: 0.8525
- Polish Mse: 0.0136
- Polish Mae: 0.0867
- Polish R2: 0.8439
- Portuguese Mse: 0.0226
- Portuguese Mae: 0.1201
- Portuguese R2: 0.7122
- Russian Mse: 0.0198
- Russian Mae: 0.1066
- Russian R2: 0.7818
- Spanish Mse: 0.0123
- Spanish Mae: 0.0815
- Spanish R2: 0.8540
- Swedish Mse: 0.0104
- Swedish Mae: 0.0783
- Swedish R2: 0.8792
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Arabic Mse | Arabic Mae | Arabic R2 | Chinese Mse | Chinese Mae | Chinese R2 | Czech Mse | Czech Mae | Czech R2 | Dutch Mse | Dutch Mae | Dutch R2 | English Mse | English Mae | English R2 | French Mse | French Mae | French R2 | German Mse | German Mae | German R2 | Hindi Mse | Hindi Mae | Hindi R2 | Indonesian Mse | Indonesian Mae | Indonesian R2 | Italian Mse | Italian Mae | Italian R2 | Japanese Mse | Japanese Mae | Japanese R2 | Korean Mse | Korean Mae | Korean R2 | Polish Mse | Polish Mae | Polish R2 | Portuguese Mse | Portuguese Mae | Portuguese R2 | Russian Mse | Russian Mae | Russian R2 | Spanish Mse | Spanish Mae | Spanish R2 | Swedish Mse | Swedish Mae | Swedish R2 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:----------:|:----------:|:---------:|:-----------:|:-----------:|:----------:|:---------:|:---------:|:--------:|:---------:|:---------:|:--------:|:-----------:|:-----------:|:----------:|:----------:|:----------:|:---------:|:----------:|:----------:|:---------:|:---------:|:---------:|:--------:|:--------------:|:--------------:|:-------------:|:-----------:|:-----------:|:----------:|:------------:|:------------:|:-----------:|:----------:|:----------:|:---------:|:----------:|:----------:|:---------:|:--------------:|:--------------:|:-------------:|:-----------:|:-----------:|:----------:|:-----------:|:-----------:|:----------:|:-----------:|:-----------:|:----------:|
| 0.047 | 0.0376 | 200 | 0.0216 | 0.0216 | 0.1134 | 0.7529 | 0.0202 | 0.1091 | 0.7828 | 0.0282 | 0.1373 | 0.6625 | 0.0165 | 0.0977 | 0.8105 | 0.0121 | 0.0861 | 0.8578 | 0.0141 | 0.0943 | 0.8505 | 0.0165 | 0.0974 | 0.8138 | 0.0344 | 0.1514 | 0.5471 | 0.0206 | 0.1147 | 0.7598 | 0.0156 | 0.0982 | 0.8252 | 0.0176 | 0.0974 | 0.7962 | 0.0214 | 0.1184 | 0.7678 | 0.0180 | 0.1104 | 0.8073 | 0.0163 | 0.0966 | 0.8132 | 0.0416 | 0.1610 | 0.4706 | 0.0294 | 0.1359 | 0.6768 | 0.0222 | 0.1117 | 0.7362 | 0.0224 | 0.1107 | 0.7396 |
| 0.0319 | 0.0753 | 400 | 0.0170 | 0.0170 | 0.0996 | 0.8058 | 0.0204 | 0.1095 | 0.7805 | 0.0215 | 0.1104 | 0.7425 | 0.0137 | 0.0889 | 0.8431 | 0.0145 | 0.0911 | 0.8301 | 0.0147 | 0.0897 | 0.8442 | 0.0123 | 0.0828 | 0.8606 | 0.0257 | 0.1308 | 0.6611 | 0.0171 | 0.0985 | 0.8005 | 0.0117 | 0.0843 | 0.8688 | 0.0120 | 0.0865 | 0.8611 | 0.0186 | 0.1023 | 0.7983 | 0.0150 | 0.0957 | 0.8395 | 0.0149 | 0.0966 | 0.8284 | 0.0233 | 0.1169 | 0.7031 | 0.0224 | 0.1155 | 0.7534 | 0.0161 | 0.0993 | 0.8084 | 0.0144 | 0.0943 | 0.8329 |
| 0.0334 | 0.1129 | 600 | 0.0218 | 0.0218 | 0.1151 | 0.7503 | 0.0183 | 0.1017 | 0.8028 | 0.0279 | 0.1313 | 0.6659 | 0.0173 | 0.1050 | 0.8019 | 0.0122 | 0.0847 | 0.8571 | 0.0149 | 0.1010 | 0.8420 | 0.0144 | 0.0959 | 0.8378 | 0.0309 | 0.1378 | 0.5929 | 0.0235 | 0.1186 | 0.7253 | 0.0199 | 0.1152 | 0.7770 | 0.0114 | 0.0808 | 0.8675 | 0.0294 | 0.1408 | 0.6815 | 0.0381 | 0.1564 | 0.5924 | 0.0192 | 0.1162 | 0.7793 | 0.0284 | 0.1311 | 0.6386 | 0.0303 | 0.1314 | 0.6659 | 0.0172 | 0.1025 | 0.7956 | 0.0174 | 0.1058 | 0.7970 |
| 0.03 | 0.1506 | 800 | 0.0258 | 0.0258 | 0.1270 | 0.7049 | 0.0327 | 0.1524 | 0.6482 | 0.0315 | 0.1333 | 0.6229 | 0.0259 | 0.1243 | 0.7022 | 0.0246 | 0.1231 | 0.7115 | 0.0167 | 0.1021 | 0.8230 | 0.0228 | 0.1202 | 0.7429 | 0.0321 | 0.1452 | 0.5774 | 0.0233 | 0.1251 | 0.7277 | 0.0214 | 0.1186 | 0.7604 | 0.0174 | 0.1076 | 0.7987 | 0.0314 | 0.1325 | 0.6594 | 0.0240 | 0.1201 | 0.7429 | 0.0196 | 0.1116 | 0.7744 | 0.0389 | 0.1636 | 0.5052 | 0.0279 | 0.1326 | 0.6930 | 0.0263 | 0.1266 | 0.6870 | 0.0217 | 0.1199 | 0.7480 |
| 0.0303 | 0.1882 | 1000 | 0.0291 | 0.0291 | 0.1374 | 0.6673 | 0.0275 | 0.1350 | 0.7046 | 0.0308 | 0.1327 | 0.6313 | 0.0364 | 0.1587 | 0.5816 | 0.0246 | 0.1281 | 0.7123 | 0.0213 | 0.1208 | 0.7752 | 0.0280 | 0.1419 | 0.6832 | 0.0454 | 0.1782 | 0.4023 | 0.0244 | 0.1305 | 0.7152 | 0.0178 | 0.1072 | 0.8006 | 0.0294 | 0.1472 | 0.6592 | 0.0312 | 0.1290 | 0.6616 | 0.0207 | 0.1092 | 0.7785 | 0.0287 | 0.1378 | 0.6701 | 0.0451 | 0.1764 | 0.4263 | 0.0304 | 0.1396 | 0.6653 | 0.0279 | 0.1332 | 0.6684 | 0.0246 | 0.1294 | 0.7138 |
| 0.024 | 0.2259 | 1200 | 0.0135 | 0.0135 | 0.0868 | 0.8450 | 0.0133 | 0.0847 | 0.8573 | 0.0187 | 0.0997 | 0.7763 | 0.0091 | 0.0744 | 0.8950 | 0.0101 | 0.0725 | 0.8819 | 0.0075 | 0.0667 | 0.9205 | 0.0085 | 0.0700 | 0.9042 | 0.0245 | 0.1183 | 0.6768 | 0.0130 | 0.0833 | 0.8477 | 0.0100 | 0.0819 | 0.8879 | 0.0080 | 0.0703 | 0.9074 | 0.0176 | 0.1001 | 0.8090 | 0.0162 | 0.0973 | 0.8270 | 0.0110 | 0.0848 | 0.8740 | 0.0211 | 0.1088 | 0.7311 | 0.0194 | 0.1033 | 0.7862 | 0.0126 | 0.0844 | 0.8502 | 0.0096 | 0.0743 | 0.8880 |
| 0.0261 | 0.2635 | 1400 | 0.0155 | 0.0155 | 0.0943 | 0.8227 | 0.0187 | 0.1054 | 0.7992 | 0.0207 | 0.1070 | 0.7523 | 0.0122 | 0.0836 | 0.8601 | 0.0149 | 0.0917 | 0.8251 | 0.0116 | 0.0835 | 0.8770 | 0.0120 | 0.0833 | 0.8646 | 0.0215 | 0.1124 | 0.7165 | 0.0136 | 0.0851 | 0.8417 | 0.0107 | 0.0835 | 0.8802 | 0.0095 | 0.0763 | 0.8895 | 0.0254 | 0.1197 | 0.7249 | 0.0151 | 0.0979 | 0.8387 | 0.0126 | 0.0854 | 0.8557 | 0.0199 | 0.1050 | 0.7474 | 0.0205 | 0.1072 | 0.7748 | 0.0127 | 0.0867 | 0.8489 | 0.0119 | 0.0884 | 0.8621 |
| 0.0305 | 0.3011 | 1600 | 0.0228 | 0.0228 | 0.1187 | 0.7390 | 0.0193 | 0.1089 | 0.7926 | 0.0273 | 0.1270 | 0.6726 | 0.0226 | 0.1149 | 0.7409 | 0.0233 | 0.1224 | 0.7270 | 0.0225 | 0.1248 | 0.7616 | 0.0197 | 0.1123 | 0.7770 | 0.0378 | 0.1623 | 0.5020 | 0.0185 | 0.1061 | 0.7841 | 0.0157 | 0.0997 | 0.8245 | 0.0179 | 0.1090 | 0.7927 | 0.0225 | 0.1071 | 0.7563 | 0.0233 | 0.1198 | 0.7508 | 0.0230 | 0.1176 | 0.7360 | 0.0334 | 0.1522 | 0.5756 | 0.0258 | 0.1280 | 0.7164 | 0.0176 | 0.1010 | 0.7906 | 0.0175 | 0.1049 | 0.7969 |
| 0.0247 | 0.3388 | 1800 | 0.0155 | 0.0155 | 0.0929 | 0.8221 | 0.0165 | 0.0965 | 0.8221 | 0.0187 | 0.0981 | 0.7762 | 0.0133 | 0.0824 | 0.8476 | 0.0157 | 0.0941 | 0.8162 | 0.0129 | 0.0860 | 0.8635 | 0.0150 | 0.0942 | 0.8305 | 0.0259 | 0.1284 | 0.6585 | 0.0133 | 0.0860 | 0.8443 | 0.0105 | 0.0802 | 0.8829 | 0.0121 | 0.0846 | 0.8600 | 0.0190 | 0.0978 | 0.7942 | 0.0130 | 0.0850 | 0.8603 | 0.0145 | 0.0886 | 0.8334 | 0.0201 | 0.1088 | 0.7445 | 0.0198 | 0.1044 | 0.7821 | 0.0129 | 0.0828 | 0.8464 | 0.0110 | 0.0816 | 0.8720 |
| 0.0238 | 0.3764 | 2000 | 0.0129 | 0.0129 | 0.0842 | 0.8521 | 0.0139 | 0.0872 | 0.8504 | 0.0165 | 0.0939 | 0.8026 | 0.0114 | 0.0777 | 0.8692 | 0.0118 | 0.0780 | 0.8616 | 0.0086 | 0.0681 | 0.9087 | 0.0097 | 0.0751 | 0.8902 | 0.0213 | 0.1092 | 0.7192 | 0.0129 | 0.0847 | 0.8498 | 0.0082 | 0.0718 | 0.9079 | 0.0078 | 0.0698 | 0.9100 | 0.0154 | 0.0932 | 0.8333 | 0.0134 | 0.0893 | 0.8564 | 0.0113 | 0.0793 | 0.8707 | 0.0187 | 0.1020 | 0.7627 | 0.0189 | 0.0998 | 0.7923 | 0.0106 | 0.0773 | 0.8738 | 0.0093 | 0.0749 | 0.8921 |
| 0.0259 | 0.4141 | 2200 | 0.0127 | 0.0127 | 0.0810 | 0.8547 | 0.0133 | 0.0827 | 0.8567 | 0.0165 | 0.0914 | 0.8026 | 0.0086 | 0.0660 | 0.9017 | 0.0097 | 0.0677 | 0.8866 | 0.0084 | 0.0613 | 0.9116 | 0.0086 | 0.0669 | 0.9023 | 0.0212 | 0.1090 | 0.7209 | 0.0129 | 0.0846 | 0.8491 | 0.0080 | 0.0692 | 0.9106 | 0.0082 | 0.0677 | 0.9045 | 0.0154 | 0.0912 | 0.8326 | 0.0154 | 0.0943 | 0.8350 | 0.0104 | 0.0761 | 0.8805 | 0.0204 | 0.1061 | 0.7407 | 0.0190 | 0.0959 | 0.7904 | 0.0104 | 0.0754 | 0.8763 | 0.0094 | 0.0717 | 0.8907 |
| 0.0227 | 0.4517 | 2400 | 0.0140 | 0.0140 | 0.0887 | 0.8398 | 0.0140 | 0.0870 | 0.8498 | 0.0165 | 0.0934 | 0.8019 | 0.0113 | 0.0791 | 0.8698 | 0.0122 | 0.0802 | 0.8571 | 0.0094 | 0.0730 | 0.9009 | 0.0117 | 0.0838 | 0.8681 | 0.0220 | 0.1135 | 0.7102 | 0.0138 | 0.0866 | 0.8392 | 0.0092 | 0.0763 | 0.8966 | 0.0091 | 0.0754 | 0.8950 | 0.0166 | 0.0950 | 0.8200 | 0.0150 | 0.0958 | 0.8398 | 0.0114 | 0.0825 | 0.8692 | 0.0225 | 0.1179 | 0.7137 | 0.0213 | 0.1079 | 0.7652 | 0.0118 | 0.0821 | 0.8600 | 0.0102 | 0.0787 | 0.8812 |
| 0.0235 | 0.4894 | 2600 | 0.0162 | 0.0162 | 0.0957 | 0.8141 | 0.0150 | 0.0910 | 0.8382 | 0.0200 | 0.1056 | 0.7608 | 0.0157 | 0.0925 | 0.8196 | 0.0168 | 0.0965 | 0.8029 | 0.0119 | 0.0818 | 0.8739 | 0.0151 | 0.0936 | 0.8289 | 0.0222 | 0.1147 | 0.7074 | 0.0164 | 0.0967 | 0.8086 | 0.0115 | 0.0826 | 0.8710 | 0.0125 | 0.0862 | 0.8553 | 0.0192 | 0.0998 | 0.7913 | 0.0139 | 0.0913 | 0.8507 | 0.0142 | 0.0888 | 0.8371 | 0.0221 | 0.1177 | 0.7183 | 0.0232 | 0.1151 | 0.7444 | 0.0139 | 0.0874 | 0.8342 | 0.0121 | 0.0851 | 0.8587 |
| 0.024 | 0.5270 | 2800 | 0.0168 | 0.0168 | 0.0973 | 0.8078 | 0.0172 | 0.0955 | 0.8151 | 0.0229 | 0.1139 | 0.7261 | 0.0134 | 0.0846 | 0.8458 | 0.0171 | 0.0969 | 0.7994 | 0.0137 | 0.0870 | 0.8551 | 0.0160 | 0.0961 | 0.8189 | 0.0211 | 0.1137 | 0.7216 | 0.0166 | 0.0980 | 0.8057 | 0.0134 | 0.0884 | 0.8506 | 0.0120 | 0.0839 | 0.8611 | 0.0180 | 0.0953 | 0.8049 | 0.0146 | 0.0911 | 0.8441 | 0.0150 | 0.0910 | 0.8278 | 0.0210 | 0.1164 | 0.7335 | 0.0237 | 0.1184 | 0.7388 | 0.0171 | 0.0970 | 0.7961 | 0.0127 | 0.0865 | 0.8524 |
| 0.0164 | 0.5647 | 3000 | 0.0214 | 0.0214 | 0.1123 | 0.7553 | 0.0212 | 0.1098 | 0.7722 | 0.0278 | 0.1305 | 0.6665 | 0.0196 | 0.1050 | 0.7749 | 0.0213 | 0.1109 | 0.7502 | 0.0196 | 0.1099 | 0.7928 | 0.0191 | 0.1061 | 0.7838 | 0.0273 | 0.1344 | 0.6397 | 0.0187 | 0.1077 | 0.7813 | 0.0163 | 0.0985 | 0.8174 | 0.0169 | 0.1000 | 0.8045 | 0.0219 | 0.1074 | 0.7628 | 0.0166 | 0.0983 | 0.8218 | 0.0202 | 0.1059 | 0.7686 | 0.0282 | 0.1370 | 0.6418 | 0.0299 | 0.1381 | 0.6707 | 0.0242 | 0.1181 | 0.7128 | 0.0146 | 0.0917 | 0.8303 |
| 0.0178 | 0.6023 | 3200 | 0.0134 | 0.0134 | 0.0853 | 0.8461 | 0.0151 | 0.0887 | 0.8377 | 0.0179 | 0.0986 | 0.7853 | 0.0110 | 0.0757 | 0.8737 | 0.0140 | 0.0862 | 0.8358 | 0.0100 | 0.0721 | 0.8946 | 0.0108 | 0.0775 | 0.8774 | 0.0222 | 0.1165 | 0.7075 | 0.0123 | 0.0823 | 0.8569 | 0.0091 | 0.0730 | 0.8977 | 0.0085 | 0.0707 | 0.9018 | 0.0155 | 0.0876 | 0.8319 | 0.0121 | 0.0824 | 0.8703 | 0.0112 | 0.0765 | 0.8715 | 0.0190 | 0.1091 | 0.7583 | 0.0199 | 0.1069 | 0.7805 | 0.0108 | 0.0747 | 0.8713 | 0.0090 | 0.0714 | 0.8948 |
| 0.0191 | 0.6399 | 3400 | 0.0165 | 0.0165 | 0.0970 | 0.8110 | 0.0176 | 0.1000 | 0.8105 | 0.0167 | 0.0954 | 0.8004 | 0.0145 | 0.0910 | 0.8340 | 0.0165 | 0.0951 | 0.8072 | 0.0129 | 0.0853 | 0.8633 | 0.0135 | 0.0882 | 0.8470 | 0.0288 | 0.1366 | 0.6210 | 0.0141 | 0.0904 | 0.8348 | 0.0114 | 0.0836 | 0.8728 | 0.0124 | 0.0866 | 0.8565 | 0.0166 | 0.0925 | 0.8201 | 0.0138 | 0.0896 | 0.8519 | 0.0147 | 0.0900 | 0.8317 | 0.0278 | 0.1351 | 0.6461 | 0.0228 | 0.1158 | 0.7489 | 0.0160 | 0.0940 | 0.8092 | 0.0106 | 0.0793 | 0.8766 |
| 0.0162 | 0.6776 | 3600 | 0.0171 | 0.0171 | 0.0994 | 0.8046 | 0.0179 | 0.1019 | 0.8076 | 0.0218 | 0.1115 | 0.7384 | 0.0149 | 0.0926 | 0.8292 | 0.0174 | 0.0985 | 0.7964 | 0.0127 | 0.0855 | 0.8660 | 0.0147 | 0.0929 | 0.8338 | 0.0266 | 0.1302 | 0.6496 | 0.0161 | 0.0984 | 0.8120 | 0.0122 | 0.0865 | 0.8637 | 0.0124 | 0.0875 | 0.8559 | 0.0198 | 0.1021 | 0.7855 | 0.0140 | 0.0903 | 0.8505 | 0.0157 | 0.0950 | 0.8201 | 0.0245 | 0.1250 | 0.6883 | 0.0230 | 0.1170 | 0.7471 | 0.0153 | 0.0919 | 0.8182 | 0.0113 | 0.0831 | 0.8680 |
| 0.0186 | 0.7152 | 3800 | 0.0187 | 0.0187 | 0.1045 | 0.7857 | 0.0183 | 0.1024 | 0.8030 | 0.0263 | 0.1252 | 0.6852 | 0.0166 | 0.0968 | 0.8094 | 0.0191 | 0.1055 | 0.7760 | 0.0151 | 0.0951 | 0.8401 | 0.0154 | 0.0953 | 0.8256 | 0.0280 | 0.1341 | 0.6315 | 0.0170 | 0.1020 | 0.8013 | 0.0134 | 0.0900 | 0.8506 | 0.0133 | 0.0898 | 0.8462 | 0.0227 | 0.1101 | 0.7540 | 0.0160 | 0.0964 | 0.8289 | 0.0178 | 0.1013 | 0.7960 | 0.0263 | 0.1303 | 0.6651 | 0.0245 | 0.1227 | 0.7302 | 0.0162 | 0.0941 | 0.8075 | 0.0123 | 0.0848 | 0.8574 |
| 0.0168 | 0.7529 | 4000 | 0.0165 | 0.0165 | 0.0969 | 0.8116 | 0.0166 | 0.0955 | 0.8217 | 0.0220 | 0.1129 | 0.7362 | 0.0141 | 0.0892 | 0.8377 | 0.0180 | 0.1002 | 0.7895 | 0.0132 | 0.0872 | 0.8604 | 0.0143 | 0.0912 | 0.8384 | 0.0236 | 0.1200 | 0.6884 | 0.0143 | 0.0903 | 0.8336 | 0.0126 | 0.0867 | 0.8595 | 0.0112 | 0.0825 | 0.8698 | 0.0196 | 0.1019 | 0.7876 | 0.0142 | 0.0918 | 0.8481 | 0.0148 | 0.0921 | 0.8296 | 0.0247 | 0.1249 | 0.6854 | 0.0215 | 0.1121 | 0.7634 | 0.0138 | 0.0861 | 0.8358 | 0.0113 | 0.0821 | 0.8690 |
| 0.0168 | 0.7905 | 4200 | 0.0133 | 0.0133 | 0.0848 | 0.8476 | 0.0144 | 0.0857 | 0.8456 | 0.0175 | 0.0981 | 0.7898 | 0.0107 | 0.0744 | 0.8773 | 0.0142 | 0.0877 | 0.8332 | 0.0097 | 0.0712 | 0.8975 | 0.0112 | 0.0790 | 0.8733 | 0.0206 | 0.1113 | 0.7287 | 0.0118 | 0.0801 | 0.8621 | 0.0097 | 0.0739 | 0.8918 | 0.0085 | 0.0706 | 0.9013 | 0.0159 | 0.0896 | 0.8278 | 0.0122 | 0.0828 | 0.8699 | 0.0115 | 0.0778 | 0.8675 | 0.0201 | 0.1117 | 0.7449 | 0.0186 | 0.1025 | 0.7947 | 0.0108 | 0.0743 | 0.8714 | 0.0090 | 0.0706 | 0.8956 |
| 0.0192 | 0.8282 | 4400 | 0.0126 | 0.0126 | 0.0829 | 0.8554 | 0.0143 | 0.0862 | 0.8465 | 0.0165 | 0.0947 | 0.8024 | 0.0101 | 0.0743 | 0.8840 | 0.0128 | 0.0820 | 0.8499 | 0.0086 | 0.0672 | 0.9088 | 0.0107 | 0.0777 | 0.8796 | 0.0198 | 0.1080 | 0.7389 | 0.0118 | 0.0795 | 0.8619 | 0.0089 | 0.0722 | 0.8999 | 0.0080 | 0.0699 | 0.9079 | 0.0149 | 0.0875 | 0.8384 | 0.0122 | 0.0842 | 0.8695 | 0.0106 | 0.0768 | 0.8785 | 0.0193 | 0.1089 | 0.7545 | 0.0176 | 0.0977 | 0.8064 | 0.0101 | 0.0731 | 0.8803 | 0.0085 | 0.0701 | 0.9006 |
| 0.017 | 0.8658 | 4600 | 0.0181 | 0.0181 | 0.1027 | 0.7929 | 0.0193 | 0.1056 | 0.7919 | 0.0235 | 0.1177 | 0.7184 | 0.0151 | 0.0912 | 0.8263 | 0.0193 | 0.1056 | 0.7744 | 0.0143 | 0.0913 | 0.8489 | 0.0160 | 0.0970 | 0.8190 | 0.0249 | 0.1260 | 0.6725 | 0.0161 | 0.0990 | 0.8118 | 0.0148 | 0.0954 | 0.8348 | 0.0134 | 0.0907 | 0.8446 | 0.0210 | 0.1059 | 0.7726 | 0.0159 | 0.0965 | 0.8300 | 0.0160 | 0.0952 | 0.8157 | 0.0279 | 0.1355 | 0.6446 | 0.0222 | 0.1158 | 0.7554 | 0.0151 | 0.0909 | 0.8206 | 0.0127 | 0.0868 | 0.8518 |
| 0.021 | 0.9034 | 4800 | 0.0146 | 0.0146 | 0.0905 | 0.8331 | 0.0161 | 0.0942 | 0.8267 | 0.0196 | 0.1046 | 0.7655 | 0.0120 | 0.0814 | 0.8619 | 0.0147 | 0.0890 | 0.8276 | 0.0106 | 0.0767 | 0.8875 | 0.0122 | 0.0840 | 0.8627 | 0.0215 | 0.1136 | 0.7170 | 0.0137 | 0.0889 | 0.8399 | 0.0109 | 0.0811 | 0.8776 | 0.0100 | 0.0779 | 0.8844 | 0.0168 | 0.0934 | 0.8177 | 0.0133 | 0.0885 | 0.8573 | 0.0126 | 0.0834 | 0.8556 | 0.0229 | 0.1200 | 0.7086 | 0.0192 | 0.1044 | 0.7891 | 0.0118 | 0.0796 | 0.8601 | 0.0100 | 0.0768 | 0.8841 |
| 0.0202 | 0.9411 | 5000 | 0.0174 | 0.0174 | 0.1007 | 0.8004 | 0.0188 | 0.1044 | 0.7975 | 0.0226 | 0.1146 | 0.7296 | 0.0152 | 0.0930 | 0.8258 | 0.0182 | 0.1017 | 0.7868 | 0.0137 | 0.0892 | 0.8550 | 0.0152 | 0.0944 | 0.8283 | 0.0224 | 0.1164 | 0.7049 | 0.0158 | 0.0970 | 0.8151 | 0.0136 | 0.0909 | 0.8483 | 0.0129 | 0.0887 | 0.8509 | 0.0200 | 0.1037 | 0.7828 | 0.0156 | 0.0964 | 0.8329 | 0.0161 | 0.0962 | 0.8148 | 0.0267 | 0.1317 | 0.6603 | 0.0223 | 0.1151 | 0.7548 | 0.0149 | 0.0911 | 0.8223 | 0.0124 | 0.0868 | 0.8552 |
| 0.0218 | 0.9787 | 5200 | 0.0149 | 0.0149 | 0.0914 | 0.8297 | 0.0165 | 0.0951 | 0.8225 | 0.0187 | 0.1023 | 0.7755 | 0.0130 | 0.0844 | 0.8506 | 0.0155 | 0.0924 | 0.8184 | 0.0109 | 0.0775 | 0.8847 | 0.0130 | 0.0870 | 0.8532 | 0.0205 | 0.1102 | 0.7295 | 0.0138 | 0.0884 | 0.8389 | 0.0112 | 0.0815 | 0.8750 | 0.0104 | 0.0789 | 0.8796 | 0.0168 | 0.0934 | 0.8177 | 0.0138 | 0.0900 | 0.8525 | 0.0136 | 0.0867 | 0.8439 | 0.0226 | 0.1201 | 0.7122 | 0.0198 | 0.1066 | 0.7818 | 0.0123 | 0.0815 | 0.8540 | 0.0104 | 0.0783 | 0.8792 |
### Framework versions
- Transformers 4.50.0
- Pytorch 2.3.0+cu118
- Datasets 2.21.0
- Tokenizers 0.21.1
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Subsets and Splits