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| likes
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11k
| library_name
stringclasses 245
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timestamp[us, tz=UTC] | card
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|---|---|---|---|---|---|---|---|---|---|
glorial/llama2-eng | glorial | 2024-07-01T05:38:17Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T05:38:17Z | Entry not found |
kmpartner/bk-testcan | kmpartner | 2024-07-01T05:44:14Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"safetensors",
"endpoints_compatible",
"diffusers:StableDiffusionControlNetPipeline",
"region:us"
] | text-to-image | 2024-07-01T05:40:32Z | Entry not found |
X27/vit-Facial-Expression-Recognition | X27 | 2024-07-01T08:41:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | image-classification | 2024-07-01T05:40:42Z | Entry not found |
yjwon/zephyr_sft_dpo_beta5e-2_epoch4 | yjwon | 2024-07-01T05:49:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T05:45:02Z | Entry not found |
Rdvs1969/WonderWoman | Rdvs1969 | 2024-07-01T05:45:26Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T05:45:25Z | Entry not found |
Jsjshshd/gptoezm | Jsjshshd | 2024-07-01T05:46:55Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T05:45:39Z | from transformers import pipeline
# Load the model from Hugging Face Transformers Hub
generator = pipeline('text-generation', model='gpt2')
# Main conversation loop
print("Starting the conversation!")
conversation_history = ""
while True:
user_input = input("User: ")
# Append user input to conversation history
conversation_history += user_input + " "
# Generate response based on the entire conversation history
response = generator(conversation_history, max_length=100, num_return_sequences=1)[0]['generated_text']
print("Model:", response)
|
noobilal/Falcon7B | noobilal | 2024-07-01T05:46:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T05:45:54Z | ---
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] |
habulaj/478498453819 | habulaj | 2024-07-01T05:48:01Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T05:47:54Z | Entry not found |
lucasbalponti/split4 | lucasbalponti | 2024-07-01T05:50:45Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:neuralmind/bert-large-portuguese-cased",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-07-01T05:49:44Z | ---
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: split4
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. -->
# split4
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3764
- Accuracy: 0.9033
## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.272 | 1.0 | 8509 | 0.3425 | 0.8802 |
| 0.2319 | 2.0 | 17018 | 0.3300 | 0.8998 |
| 0.2046 | 3.0 | 25527 | 0.3764 | 0.9033 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
|
jykim310/st-llama-1-5.5b-taylor-q4f16_1-MLC | jykim310 | 2024-07-01T05:56:14Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T05:53:48Z | Entry not found |
BilalRana/mt0-large-ia3 | BilalRana | 2024-07-01T05:54:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T05:54:28Z | ---
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] |
mihirkothari0702/Test_model | mihirkothari0702 | 2024-07-01T06:01:05Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:00:02Z | Entry not found |
locking4451/lama222 | locking4451 | 2024-07-01T06:14:31Z | 0 | 0 | null | [
"arxiv:1910.09700",
"license:llama3",
"region:us"
] | null | 2024-07-01T06:01:31Z | ---
license: llama3
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **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] |
yjwon/zephyr_sft_dpo_beta1e-1_epoch5 | yjwon | 2024-07-01T06:06:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:01:59Z | Entry not found |
abdiharyadi/indoamrbart-mbart-triple-ft-parser-no-nst-16-eps-v2 | abdiharyadi | 2024-07-01T06:12:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"dataset:data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text2text-generation | 2024-07-01T06:04:18Z | ---
tags:
- generated_from_trainer
datasets:
- data
model-index:
- name: indoamrbart-mbart-triple-ft-parser-no-nst-16-eps-v2
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. -->
# indoamrbart-mbart-triple-ft-parser-no-nst-16-eps-v2
This model was trained from scratch on the data dataset.
## 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-06
- train_batch_size: 5
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 200
- num_epochs: 16.0
- label_smoothing_factor: 0.1
### Training results
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|
VKapseln475/Safran7885 | VKapseln475 | 2024-07-01T06:08:39Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:08:09Z | # Safran Premium France Commentaires - Safran Premium Expériences Avantages, Prix, acheter
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## **[cliquez ici pour acheter maintenant sur le site officiel de Safran Premium](https://adtocart.xyz/safran-premium-fr)**
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## La posologie de Safran Premium
La posologie recommandée pour le Safran Premium est de prendre une gélule le matin et une gélule le soir, de préférence une heure avant le coucher. Chaque flacon contient 120 gélules, ce qui correspond à un approvisionnement de deux mois si utilisé comme indiqué.
Pour maximiser les bienfaits du complément, il est conseillé de le prendre régulièrement et conformément aux instructions. Une utilisation cohérente, combinée à un mode de vie sain, permettra d’observer les meilleurs résultats.
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Somnolence ou étourdissements
Réactions allergiques, bien que rares
## Contre-indications :
Femmes enceintes ou allaitantes : la sécurité du safran pendant la grossesse et l’allaitement n’étant pas établie, il est conseillé d’éviter son utilisation.
Personnes sous médication : Ceux qui prennent des médicaments, en particulier des antidépresseurs ou des anticoagulants, devraient consulter un professionnel de santé avant de commencer le traitement.
Enfants : Safran Premium n’est pas recommandé pour les enfants sans l’avis d’un médecin.
En résumé, bien que Safran Premium soit une option naturelle pour améliorer le bien-être, respectez la posologie recommandée et de prendre en compte les éventuelles interactions médicamenteuses ou conditions de santé préexistantes.
## Où acheter Safran Premium ?
Le Safran Premium de Nutr’Innov est un produit exclusif qui n’est disponible à l’achat que via le site officiel du fabricant. Cette décision de distribution exclusive est stratégique et repose sur plusieurs raisons importantes. D’abord, elle garantit que les clients reçoivent le produit authentique, directement du fabricant, sans intermédiaire susceptible d’altérer la qualité ou d’augmenter les prix.
## **[cliquez ici pour acheter maintenant sur le site officiel de Safran Premium](https://adtocart.xyz/safran-premium-fr)** |
khanhnn55/naschainv10 | khanhnn55 | 2024-07-02T23:12:47Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:08:27Z | Entry not found |
Moriacrafter/Qwen1.5-1.8B-8bit_DepressionDetection | Moriacrafter | 2024-07-01T06:10:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:08:49Z | ---
library_name: transformers
tags:
- llama-factory
---
# 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]
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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<!-- 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
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[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. -->
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
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<!-- 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. -->
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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]
- **Hours used:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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yjwon/zephyr_sft_dpo_beta5e-2_epoch5 | yjwon | 2024-07-01T06:12:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:08:56Z | Entry not found |
Ranhui/Reinforce-CartPole-v1 | Ranhui | 2024-07-01T06:11:00Z | 0 | 0 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | reinforcement-learning | 2024-07-01T06:10:48Z | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
verified: false
---
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
|
soonmo/OpenHermes-2.5-Mistral-7B-method1 | soonmo | 2024-07-01T06:36:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:11:30Z | ---
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] |
SeanYou/gpt-sovits-firefly | SeanYou | 2024-07-01T06:12:41Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T06:12:41Z | ---
license: mit
---
|
yjwon/zephyr_sft_dpo_beta1e-2_epoch5 | yjwon | 2024-07-01T06:17:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:13:15Z | Entry not found |
moonjeongy/yujin | moonjeongy | 2024-07-01T06:16:00Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:14:54Z | Entry not found |
LeroyDyer/LCARS_AI_016 | LeroyDyer | 2024-07-01T06:22:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"en",
"base_model:LCARS_AI_015",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T06:17:19Z | ---
base_model: LCARS_AI_015
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** LeroyDyer
- **License:** apache-2.0
- **Finetuned from model :** LCARS_AI_015
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)
|
vaivTA/yolov8x_doclaynet | vaivTA | 2024-07-03T00:00:19Z | 0 | 0 | null | [
"tensorboard",
"object-detection",
"en",
"dataset:ds4sd/DocLayNet",
"license:mit",
"region:us"
] | object-detection | 2024-07-01T06:17:40Z | ---
license: mit
datasets:
- ds4sd/DocLayNet
language:
- en
metrics:
- accuracy
pipeline_tag: object-detection
--- |
nandhakumar7/sample | nandhakumar7 | 2024-07-01T06:18:41Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:18:41Z | Entry not found |
heison/l3 | heison | 2024-07-01T06:20:33Z | 0 | 0 | null | [
"license:llama3",
"region:us"
] | null | 2024-07-01T06:20:33Z | ---
license: llama3
---
|
peshimaammuzammil/imageteller | peshimaammuzammil | 2024-07-01T06:23:07Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:22:08Z | Entry not found |
yjwon/zephyr_sft_uniform_meogd_rms_RE_epoch1 | yjwon | 2024-07-01T06:31:32Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:27:08Z | Entry not found |
shivangi19s/llama3_chatbot_finetuned | shivangi19s | 2024-07-01T06:27:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:27:42Z | Entry not found |
apwic/summarization-base-3 | apwic | 2024-07-01T09:45:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"id",
"base_model:LazarusNLP/IndoNanoT5-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text2text-generation | 2024-07-01T06:28:24Z | ---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-base-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. -->
# summarization-base-3
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5374
- Rouge1: 0.4096
- Rouge2: 0.0
- Rougel: 0.4081
- Rougelsum: 0.4102
- Gen Len: 1.0
## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.6296 | 1.0 | 3568 | 0.5221 | 0.3678 | 0.0 | 0.3666 | 0.3673 | 1.0 |
| 0.4308 | 2.0 | 7136 | 0.4927 | 0.4034 | 0.0 | 0.3999 | 0.4032 | 1.0 |
| 0.3347 | 3.0 | 10704 | 0.5028 | 0.4081 | 0.0 | 0.407 | 0.4083 | 1.0 |
| 0.2655 | 4.0 | 14272 | 0.5221 | 0.4264 | 0.0 | 0.4239 | 0.4268 | 1.0 |
| 0.2179 | 5.0 | 17840 | 0.5374 | 0.4096 | 0.0 | 0.4081 | 0.4102 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|
mago18/ava-50-chose | mago18 | 2024-07-01T06:31:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T06:30:41Z | ---
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] |
LeroyDyer/LCARS_AI_016_4_BIT | LeroyDyer | 2024-07-01T06:33:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"sft",
"en",
"base_model:LCARS_AI_015",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text-generation | 2024-07-01T06:31:24Z | ---
base_model: LCARS_AI_015
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
- sft
---
# Uploaded model
- **Developed by:** LeroyDyer
- **License:** apache-2.0
- **Finetuned from model :** LCARS_AI_015
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)
|
yjwon/zephyr_sft_uniform_ogd_rms_RE_epoch1 | yjwon | 2024-07-01T06:36:03Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:31:58Z | Entry not found |
xinghaow/zephyr-7b-dpo-full | xinghaow | 2024-07-02T14:14:45Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"moss2",
"feature-extraction",
"custom_code",
"region:us"
] | feature-extraction | 2024-07-01T06:33:36Z | Entry not found |
ShapeKapseln33/RediminPolska76 | ShapeKapseln33 | 2024-07-01T06:35:53Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:33:52Z | Redimin Polska Opinie Stosując ten produkt, można zapomnieć o ciągłych dietach i wyczerpujących treningach cardio, ponieważ sam rozwiązuje problem nadwagi. Dowiedzmy się więcej o tym, czym jest Redimin?
**[Kliknij tutaj, aby kupić teraz na oficjalnej stronie Redmi Polska](https://adtocart.xyz/redimin-polska)**
Utrata wagi to cel wielu ludzi, ale znalezienie czasu na ćwiczenia może być trudne, ze względu na styl życia. Jeśli jesteś chętny do utraty wagi, ale nie masz zbyt wiele czasu, aby spędzić go na siłowni, nie martw się – istnieje wiele sposobów, aby zrzucić zbędne kilogramy bez ogromu wyrzeczeń. Taką pomocną dłonią jest Redimin – suplement diety, który wspomaga proces utraty wagi.
Możesz wprowadzić małe, proste zmiany do swojej codziennej rutyny, które pomogą Ci osiągnąć cele związane z utratą wagi bez konieczności poświęcania sporo czasu na ćwiczenia.
Zdrowe odżywianie, kontrola porcji i modyfikacje stylu życia mogą być skutecznymi strategiami zrzucania tych dodatkowych kilogramów. Przy odrobinie wysiłku i niesłabnącej motywacji, można osiągnąć swoje cele utraty wagi bez większego problemu. Nie zniechęcaj się więc, jeśli nie masz czasu na ćwiczenia – nadal istnieje wiele sposobów na uzyskanie ciała, o którym zawsze marzyłeś.
Poniżej omówiony zostanie każdy aspekt suplementu Redimin, dzięki czemu dowiesz się czy jest to produkt dla Ciebie oraz co na jego temat uważają użytkownicy. Cały tekst powstał w oparciu o informacje znajdujące się na oficjalnej stronie producenta.
##Co to jest Redimin?
Redimin to suplement diety zaprojektowany, aby pomóc ludziom osiągnąć ich cele związane z utratą wagi poprzez zapewnienie naturalnego, bezpiecznego i skutecznego rozwiązania. Ten suplement jest w postaci tabletek, wykonanych z całkowicie naturalnych składników, które zostały zaprojektowane, aby pomóc przyspieszyć metabolizm i oczyścić organizm. Może pomóc osobom zmagającym się z przyrostem masy ciała, ponieważ działa na fizyczne przyczyny, takie jak powolny metabolizm i retencja płynów. Dzięki całkowicie naturalnemu składowi, Redimin z pewnością zapewni zauważalne wyniki w krótkim czasie.
Produkt Redimin jest doskonałym rozwiązaniem dla osób dorosłych, które szukają szybkiej i łatwej utraty wagi. Te kapsułki są przeznaczone do wspomagania spalania tłuszczu bez konieczności wprowadzania drastycznych zmian w diecie lub ćwiczeń, co czyni je odpowiednią opcją dla każdej osoby, która chce zrzucić trochę kilogramów, ale nie wiem od czego zacząć.
Dzięki wygodnym i skutecznym właściwościom spalającym tłuszcz, Redimin jest doskonałym rozwiązaniem dla każdego, kto szuka bezstresowego i szybkiego sposobu na osiągnięcie swoich celów związanych z utratą wagi.
**[Kliknij tutaj, aby kupić teraz na oficjalnej stronie Redmi Polska](https://adtocart.xyz/redimin-polska)**
##Jak działa Redimin?
Redimin to suplement diety zaprojektowany, aby pomóc organizmowi spalić nadmiar tłuszczu, nawet podczas snu. Redimin działa poprzez przyspieszenie metabolizmu, dzięki czemu organizm może szybciej wchłaniać i trawić pokarm. Ponadto suplement może pomóc zaaklimatyzować organizm do poczucia sytości i pełności, zmniejszając tym samym głód. Aby zmaksymalizować jego działanie, ważne jest, aby połączyć stosowanie Redimin z dietą o niskiej zawartości tłuszczu i cukru oraz regularną aktywnością fizyczną. W ten sposób Redimin może pomóc w przywróceniu ciała do formy bez poświęcania wielu godzin każdego dnia na ćwiczenia.
##Redimin – Skład
Poszczególne skład, które tworzą Redimin są wolne od wszelkich sztucznych dodatków i niebezpiecznych substancji chemicznych, dzięki czemu są wysoce tolerowane i skuteczne dla większości ludzi, którzy je przyjmują. Poniżej znajduje się lista kompozycji występujących w Rediminie.
Bacopa Monnieri to naturalny składnik związany z wieloma niezwykłymi korzyściami związanymi z utratą wagi. Pomaga regulować poziom glikemii, ograniczając gromadzenie się tłuszczu.
Berberynie przypisuje się właściwości hipoglikemiczne i jest ona stosowana jako środek wspomagający w dietach odchudzających.
L-karnityna umożliwia poprawę drenażu płynów, co pomaga wydalić nadmiar odpadów i toksyn z organizmu, oczyszczając go i umożliwiając sprawniejsze działanie funkcji życiowych.
Garcinia cambogia przyspiesza metabolizm tłuszczów i pomaga zmniejszyć głód, ułatwiając trzymanie się celów związanych z utratą wagi.
##Redimin – Efekty
Skład Redimin oferują kilka efekty, w tym zmniejszenie wzdęcia brzucha, optymalizację faz trawienia i jelit, oczyszczanie organizmu i zmniejszenie masy tłuszczu. Efekty te współpracują ze sobą, aby promować poprawę ogólnego stanu zdrowia, umożliwiając organizmowi bardziej efektywne wchłanianie niezbędnych witamin i minerałów. Redimin zawiera mieszankę starannie dobranych składników pochodzenia naturalnego, które współdziałają w celu stymulowania naturalnych procesów metabolicznych organizmu. Połączenie tych składników pomaga przyspieszyć metabolizm, reguluje poziom hormonów, wspomaga utratę wagi i zmniejsza stan zapalny. Antyoksydanty obecne w Redimin pomagają zwalczać wolne rodniki, które mogą negatywnie wpływać na proces utraty wagi.
**[Kliknij tutaj, aby kupić teraz na oficjalnej stronie Redmi Polska](https://adtocart.xyz/redimin-polska)**
##Redimin – Opinie i recenzje
Redimin stał się popularnym suplementem diety dzięki udanej sprzedaży online. Opinie użytkowników na temat Redimin są w przeważającej mierze pozytywne, z wielu konsumentów zgłaszających uczucie lżejsze, mniej wzdęty i o zmniejszone uczucie głodu po początkowym spożyciu. Ten suplement jest również bardzo chwalony za jego 100% naturalną, bezpieczną formułę bez przeciwwskazań. Ponadto zauważono, że Redimin jest łatwy do podjęcia i może pomóc w przyspieszeniu metabolizmu. Nie udało nam się znaleźć żadnych negatywnych recenzji tego produktu.
##Redimin – Dawkowanie – Sposób użycia
Zalecana dawka to dwie kapsułki dziennie, przyjmowane po jednej kapsułce 30 minut przed posiłkiem. Kapsułki Redimin należy zawsze popijać pełną szklanką wody. Należy również pamiętać, aby nie przekraczać dziennej dawki, która jest zalecana przez producenta. Producent zaleca przyjmowanie Redimin przez okres co najmniej czterech – ośmiu tygodni w celu uzyskania najlepszych rezultatów. Dłuższe stosowanie suplementu może być korzystne dla wsparcia i utrzymania utraty wagi.
##Redimin – Skutki uboczne i przeciwwskazania
Redimin jest suplementem diety, który jest ogólnie dobrze tolerowany i nie ma znanych skutków ubocznych lub przeciwwskazań i powinien być przyjmowany przez dorosłych. Jednakże, jeśli jesteś kobietą w ciąży lub karmiącą piersią, upewnij się, że skonsultujesz się z lekarzem przed zażyciem Rediminu. Dla osób, które mają alergie, pamiętaj, aby sprawdzić skład Rediminu.
##Gdzie kupić Redimin? Apteka, Allegro
Jeśli chcesz kupić autentyczny produkt Redimin, należy pamiętać o odpowiednim wyborzu miejsce zakupu. Aby uniknąć wszelkich podróbek, lepiej nie próbować znaleźć suplementu na stronach takich jak Allegro i Ebay. Ważne jest, aby kupować tylko z oficjalnej strony producenta, aby upewnić się, że otrzymujesz oryginalny produkt Redimin. Ponadto, suplement zgodnie ze strategia producenta, nie jest dostępny w aptekach.
##Ile kosztuje Redimin – Cena
Redimin jest dostępny tylko na swojej oficjalnej stronie internetowej i jego cena różni się w zależności od pakietu, który zakupisz. Cena 30 kapsułek wynosi 294 zł, ale dzięki obowiązującej teraz promocji, można zamówić kapsułki za jedyne 147 złotych z darmową dostawą. Producent Redimin oferuje promocyjną zniżkę od czasu do czasu, aby skorzystać z tego rabatu warto dokonać zamówienia jak najszybciej, gdyż jest to oferta ograniczona czasowo.
**[Kliknij tutaj, aby kupić teraz na oficjalnej stronie Redmi Polska](https://adtocart.xyz/redimin-polska)**
|
Vikas4Bits/vicuna-13b-v1.5_4bit | Vikas4Bits | 2024-07-01T06:47:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"awq",
"region:us"
] | text-generation | 2024-07-01T06:35:08Z | Entry not found |
wardloyson/d | wardloyson | 2024-07-01T06:35:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:35:12Z | Entry not found |
penguindustin/temp-model | penguindustin | 2024-07-01T06:36:38Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:35:24Z | Entry not found |
sivakarri/roberta_nba_v2 | sivakarri | 2024-07-01T10:28:17Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-07-01T06:36:18Z | ---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta_nba_v2
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. -->
# roberta_nba_v2
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8231
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4838 | 1.0 | 193 | 0.5098 |
| 0.4339 | 2.0 | 386 | 0.5224 |
| 0.3639 | 3.0 | 579 | 0.5431 |
| 0.4189 | 4.0 | 772 | 0.4780 |
| 0.3729 | 5.0 | 965 | 0.6443 |
| 0.1509 | 6.0 | 1158 | 0.6412 |
| 0.0923 | 7.0 | 1351 | 0.7526 |
| 0.0256 | 8.0 | 1544 | 0.7852 |
| 0.1447 | 9.0 | 1737 | 0.8347 |
| 0.0011 | 10.0 | 1930 | 0.8231 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
|
MayurPai/half_precision_llama2_1 | MayurPai | 2024-07-01T07:23:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:36:23Z | Entry not found |
yjwon/zephyr_sft_uniform_meogd_rms_RE_epoch2 | yjwon | 2024-07-01T06:40:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:36:35Z | Entry not found |
MrDorian/Gladiatorlight | MrDorian | 2024-07-01T06:40:50Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:38:41Z | Entry not found |
irusl/01IR-11 | irusl | 2024-07-01T06:42:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T06:39:14Z | Entry not found |
yjwon/zephyr_sft_uniform_ogd_rms_RE_epoch2 | yjwon | 2024-07-01T06:45:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:41:11Z | Entry not found |
liujiahao/Phi-3-medium-4k-instruct-lora-afac-track2 | liujiahao | 2024-07-02T05:37:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T06:42:34Z | ---
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.
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[More Information Needed]
## Bias, Risks, and Limitations
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<!-- 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
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[More Information Needed]
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[More Information Needed]
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#### Preprocessing [optional]
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#### 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. -->
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[More Information Needed]
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<!-- Relevant interpretability work for the model goes here -->
[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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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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mooskim/distilhubert-finetuned-gtzan | mooskim | 2024-07-01T07:21:20Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"hubert",
"audio-classification",
"endpoints_compatible",
"region:us"
] | audio-classification | 2024-07-01T06:44:15Z | Entry not found |
irusl/02IR-11 | irusl | 2024-07-01T06:47:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T06:45:11Z | Entry not found |
yjwon/zephyr_sft_uniform_meogd_rms_RE_epoch3 | yjwon | 2024-07-01T06:49:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:45:36Z | Entry not found |
liuqinqguan/modeltest | liuqinqguan | 2024-07-01T06:49:45Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:47:32Z | Entry not found |
tgrhn/wav2vec2-turkish-1 | tgrhn | 2024-07-01T10:34:00Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T06:48:47Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- 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.
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### 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
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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]
#### 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).
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yjwon/zephyr_sft_uniform_ogd_rms_RE_epoch3 | yjwon | 2024-07-01T06:53:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:50:04Z | Entry not found |
irusl/04IR-11 | irusl | 2024-07-01T06:53:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T06:50:59Z | Entry not found |
Tonole/test | Tonole | 2024-07-01T06:52:05Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:52:05Z | Entry not found |
azadeh1972/fVSb_finetuned | azadeh1972 | 2024-07-02T23:30:57Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"audio-classification",
"endpoints_compatible",
"region:us"
] | audio-classification | 2024-07-01T06:53:59Z | Invalid username or password. |
Aina69/opus_mt_mg_fr | Aina69 | 2024-07-01T06:54:10Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:54:10Z | Entry not found |
yjwon/zephyr_sft_uniform_meogd_rms_RE_epoch4 | yjwon | 2024-07-01T06:58:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:54:24Z | Entry not found |
whizzzzkid/whizzzzkid_358_1 | whizzzzkid | 2024-07-01T06:56:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T06:55:37Z | Entry not found |
Aina69/opus_mt_mg_eng | Aina69 | 2024-07-01T06:55:45Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T06:55:45Z | Entry not found |
siddhant2610/Llama-2-7b-chat-finetune | siddhant2610 | 2024-07-01T06:56:20Z | 0 | 0 | null | [
"license:llama2",
"region:us"
] | null | 2024-07-01T06:56:20Z | ---
license: llama2
---
|
CatBarks/t5-lora-squad_model | CatBarks | 2024-07-01T06:58:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T06:58:16Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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CatBarks/t5-lora-squad_tokenizer | CatBarks | 2024-07-01T06:58:21Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T06:58:20Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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- **Hardware Type:** [More Information Needed]
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yjwon/zephyr_sft_uniform_ogd_rms_RE_epoch4 | yjwon | 2024-07-01T07:02:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T06:58:39Z | Entry not found |
Vikas4Bits/Llama-3-8B-instruct-4bit | Vikas4Bits | 2024-07-01T09:23:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"awq",
"region:us"
] | text-generation | 2024-07-01T07:02:43Z | ## How to use
This repository contains two versions of Meta-Llama-3-8B-Instruct, for use with transformers and with the original `llama3` codebase.
### Use with transformers
You can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the `generate()` function. Let's see examples of both.
#### Transformers pipeline
```python
import transformers
import torch
model_id = "Vikas4Bits/Llama-3-8B-instruct-4bit"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
{"role": "user", "content": "Who are you?"},
]
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
messages,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
print(outputs[0]["generated_text"][-1])
```
#### Transformers AutoModelForCausalLM
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "Vikas4Bits/Llama-3-8B-instruct-4bit"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
{"role": "user", "content": "Who are you?"},
]
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
terminators = [
tokenizer.eos_token_id,
tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = model.generate(
input_ids,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
```
### Use with `llama3`
|
yjwon/zephyr_sft_uniform_meogd_rms_RE_epoch5 | yjwon | 2024-07-01T07:07:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T07:03:09Z | Entry not found |
nlplabtdtu/vilaw-sailor-instruct-v2-adapter | nlplabtdtu | 2024-07-01T07:35:20Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2024-07-01T07:03:23Z | Entry not found |
jung0202/llama3data_sample | jung0202 | 2024-07-01T07:03:35Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T07:03:35Z | ---
license: mit
---
|
Alifnfa/model_kue_indonesia | Alifnfa | 2024-07-01T07:06:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:06:42Z | Entry not found |
vimal10/example-model | vimal10 | 2024-07-01T08:34:27Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:06:51Z | Example Model
This is my model card Readme
---
license: mit
---
|
yjwon/zephyr_sft_uniform_ogd_rms_RE_epoch5 | yjwon | 2024-07-01T07:11:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T07:07:29Z | Entry not found |
whizzzzkid/whizzzzkid_359_2 | whizzzzkid | 2024-07-01T07:09:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T07:07:41Z | Entry not found |
Gaby1306/DriehoekNoord | Gaby1306 | 2024-07-01T07:09:43Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:09:43Z | Entry not found |
whizzzzkid/whizzzzkid_360_6 | whizzzzkid | 2024-07-01T07:11:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T07:09:46Z | Entry not found |
itay-nakash/model_643111dcc3_sweep_tough-blaze-1007 | itay-nakash | 2024-07-01T07:11:44Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:11:44Z | Entry not found |
whizzzzkid/whizzzzkid_361_5 | whizzzzkid | 2024-07-01T07:13:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T07:11:59Z | Entry not found |
Loren85/Dick | Loren85 | 2024-07-01T07:13:48Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-01T07:12:38Z | ---
license: openrail
---
|
whizzzzkid/whizzzzkid_362_4 | whizzzzkid | 2024-07-01T07:15:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T07:14:23Z | Entry not found |
Tanysha/llama-3-8b-chatdoc | Tanysha | 2024-07-01T07:18:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T07:17:54Z | ---
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]
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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
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[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
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
[More Information Needed]
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#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
#### Metrics
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[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]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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## Model Card Contact
[More Information Needed] |
VinaySukhesh/gemma-2-9b-q4f16_1-MLC | VinaySukhesh | 2024-07-01T07:17:56Z | 0 | 0 | null | [
"license:gemma",
"region:us"
] | null | 2024-07-01T07:17:56Z | ---
license: gemma
---
|
subhadeep-das/toyota-corolla-cross-xle-2022 | subhadeep-das | 2024-07-01T07:18:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:18:12Z | Entry not found |
scenario-labs/FastSam | scenario-labs | 2024-07-01T07:35:39Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:19:37Z | Entry not found |
davis0577/TestGPT1 | davis0577 | 2024-07-01T07:20:24Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T07:20:24Z | ---
license: mit
---
|
giusebello/garment_designer | giusebello | 2024-07-01T09:41:53Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:21:03Z | Entry not found |
habulaj/3245350643 | habulaj | 2024-07-01T07:22:13Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:22:04Z | Entry not found |
kaya-kedi/Sonic-RogerCraigSmith-TITANPretrain | kaya-kedi | 2024-07-01T07:35:14Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:23:29Z | Entry not found |
Huy227/adapter_v8 | Huy227 | 2024-07-01T07:26:23Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"llama-factory",
"lora",
"generated_from_trainer",
"base_model:google/gemma-2-9b-it",
"license:other",
"region:us"
] | null | 2024-07-01T07:25:27Z | ---
license: other
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: google/gemma-2-9b-it
model-index:
- name: dpo
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. -->
# dpo
This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the dpo_vi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5875
- Rewards/chosen: 0.7433
- Rewards/rejected: 0.4637
- Rewards/accuracies: 0.6538
- Rewards/margins: 0.2796
- Logps/rejected: -233.8130
- Logps/chosen: -211.9995
- Logits/rejected: -2.6008
- Logits/chosen: -3.2426
## 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-06
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1 |
xinqiwei/xinqi-wei | xinqiwei | 2024-07-01T07:27:08Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-07-01T07:27:08Z | ---
license: apache-2.0
---
|
soonmo/Phi-3-mini-4k-instruct-dpo_method1 | soonmo | 2024-07-02T03:54:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"conversational",
"custom_code",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T07:27:42Z | ---
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] |
itay-nakash/model_643111dcc3_sweep_cerulean-snowball-1009 | itay-nakash | 2024-07-01T07:27:50Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:27:50Z | Entry not found |
AzureBP/Yi-6B-Chat-Test1 | AzureBP | 2024-07-01T07:55:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T07:28:08Z | ---
license: mit
---
|
Imvignesh/tt-oilwell-qa-pipeline-demo | Imvignesh | 2024-07-01T07:35:11Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:28:22Z | Entry not found |
yews1234/inje-jun-yeop-en-to-ko | yews1234 | 2024-07-01T07:29:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T07:29:03Z | ---
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] |
habulaj/150713127895 | habulaj | 2024-07-01T07:30:16Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:30:09Z | Entry not found |
haibaraconan/a | haibaraconan | 2024-07-01T07:36:16Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:31:43Z | Entry not found |
Ksgk-fy/ecoach_philippine_v9_merge | Ksgk-fy | 2024-07-01T07:34:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T07:32:29Z | ---
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]
|
itay-nakash/model_2eb3b834b5_sweep_sage-energy-1010 | itay-nakash | 2024-07-01T07:34:54Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:34:54Z | Entry not found |
Kshitiz91/Llama-2-7b-chat-finetune | Kshitiz91 | 2024-07-01T07:35:18Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2024-07-01T07:35:18Z | ---
license: mit
---
|
leva4656/tsoi | leva4656 | 2024-07-01T07:46:10Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-01T07:37:36Z | ---
license: openrail
---
|
J5Tsai/debug-static-files | J5Tsai | 2024-07-01T07:42:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T07:37:45Z | Entry not found |
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