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tanaymehta/gpt2_12H_2L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:03:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:03:42Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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## Model Details
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ximbi/autoeficient | ximbi | 2024-07-01T09:03:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:03:48Z | Entry not found |
tanaymehta/gpt2_12H_4L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:03:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:03:49Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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tanaymehta/gpt2_12H_6L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:04:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:03:57Z | ---
library_name: transformers
tags: []
---
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tanaymehta/gpt2_12H_8L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:04:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:04:06Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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## Model Details
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[More Information Needed]
## Training Details
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ximbi1/autoseficient | ximbi1 | 2024-07-01T09:04:40Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:04:40Z | Entry not found |
marthakk/detr_finetuned_airdataset | marthakk | 2024-07-01T10:27:56Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"conditional_detr",
"object-detection",
"generated_from_trainer",
"dataset:dsi",
"base_model:microsoft/conditional-detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | object-detection | 2024-07-01T09:06:22Z | ---
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
datasets:
- dsi
model-index:
- name: detr_finetuned_airdataset
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. -->
# detr_finetuned_airdataset
This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the dsi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8959
- Map: 0.3195
- Map 50: 0.7784
- Map 75: 0.1925
- Map Small: 0.3211
- Map Medium: 0.0079
- Map Large: -1.0
- Mar 1: 0.0256
- Mar 10: 0.1995
- Mar 100: 0.487
- Mar Small: 0.4896
- Mar Medium: 0.0061
- Mar Large: -1.0
- Map Falciparum Trophozoite: 0.3195
- Mar 100 Falciparum Trophozoite: 0.487
- Map Wbc: -1.0
- Mar 100 Wbc: -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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Falciparum Trophozoite | Mar 100 Falciparum Trophozoite | Map Wbc | Mar 100 Wbc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:--------------------------:|:------------------------------:|:-------:|:-----------:|
| No log | 1.0 | 209 | 1.2206 | 0.1424 | 0.401 | 0.07 | 0.1429 | 0.0328 | -1.0 | 0.0168 | 0.1239 | 0.4185 | 0.4204 | 0.0612 | -1.0 | 0.1424 | 0.4185 | -1.0 | -1.0 |
| No log | 2.0 | 418 | 1.1354 | 0.2136 | 0.585 | 0.1077 | 0.2145 | 0.0224 | -1.0 | 0.0212 | 0.1608 | 0.4102 | 0.4123 | 0.0224 | -1.0 | 0.2136 | 0.4102 | -1.0 | -1.0 |
| 1.3747 | 3.0 | 627 | 1.0729 | 0.2353 | 0.6428 | 0.1092 | 0.2365 | 0.0229 | -1.0 | 0.0216 | 0.1669 | 0.4247 | 0.4268 | 0.0245 | -1.0 | 0.2353 | 0.4247 | -1.0 | -1.0 |
| 1.3747 | 4.0 | 836 | 1.0260 | 0.2548 | 0.6701 | 0.1339 | 0.2563 | 0.0178 | -1.0 | 0.0234 | 0.1792 | 0.4424 | 0.4447 | 0.0163 | -1.0 | 0.2548 | 0.4424 | -1.0 | -1.0 |
| 1.0467 | 5.0 | 1045 | 1.0116 | 0.2576 | 0.6811 | 0.1321 | 0.2589 | 0.0208 | -1.0 | 0.0229 | 0.1773 | 0.4422 | 0.4445 | 0.0184 | -1.0 | 0.2576 | 0.4422 | -1.0 | -1.0 |
| 1.0467 | 6.0 | 1254 | 1.0150 | 0.2526 | 0.6842 | 0.1191 | 0.2537 | 0.0089 | -1.0 | 0.0226 | 0.1724 | 0.4463 | 0.4486 | 0.0082 | -1.0 | 0.2526 | 0.4463 | -1.0 | -1.0 |
| 1.0467 | 7.0 | 1463 | 0.9933 | 0.2627 | 0.699 | 0.1376 | 0.2639 | 0.0211 | -1.0 | 0.0215 | 0.1773 | 0.4458 | 0.4481 | 0.0224 | -1.0 | 0.2627 | 0.4458 | -1.0 | -1.0 |
| 0.9905 | 8.0 | 1672 | 0.9642 | 0.2797 | 0.7188 | 0.1511 | 0.2809 | 0.0112 | -1.0 | 0.0241 | 0.1858 | 0.459 | 0.4614 | 0.0143 | -1.0 | 0.2797 | 0.459 | -1.0 | -1.0 |
| 0.9905 | 9.0 | 1881 | 0.9641 | 0.2786 | 0.7209 | 0.1453 | 0.2803 | 0.0103 | -1.0 | 0.0231 | 0.1861 | 0.4534 | 0.4558 | 0.0102 | -1.0 | 0.2786 | 0.4534 | -1.0 | -1.0 |
| 0.955 | 10.0 | 2090 | 0.9869 | 0.2685 | 0.7158 | 0.1366 | 0.27 | 0.0023 | -1.0 | 0.0225 | 0.1789 | 0.4442 | 0.4465 | 0.0041 | -1.0 | 0.2685 | 0.4442 | -1.0 | -1.0 |
| 0.955 | 11.0 | 2299 | 0.9612 | 0.2837 | 0.7238 | 0.1534 | 0.2856 | 0.0067 | -1.0 | 0.0242 | 0.1878 | 0.4568 | 0.4592 | 0.0082 | -1.0 | 0.2837 | 0.4568 | -1.0 | -1.0 |
| 0.9248 | 12.0 | 2508 | 0.9437 | 0.2938 | 0.7368 | 0.1635 | 0.2954 | 0.005 | -1.0 | 0.0239 | 0.1882 | 0.4701 | 0.4727 | 0.0041 | -1.0 | 0.2938 | 0.4701 | -1.0 | -1.0 |
| 0.9248 | 13.0 | 2717 | 0.9390 | 0.289 | 0.7371 | 0.16 | 0.2903 | 0.0149 | -1.0 | 0.0254 | 0.191 | 0.4685 | 0.471 | 0.0122 | -1.0 | 0.289 | 0.4685 | -1.0 | -1.0 |
| 0.9248 | 14.0 | 2926 | 0.9321 | 0.2986 | 0.7428 | 0.1744 | 0.3002 | 0.005 | -1.0 | 0.0251 | 0.1928 | 0.4743 | 0.4768 | 0.0041 | -1.0 | 0.2986 | 0.4743 | -1.0 | -1.0 |
| 0.9027 | 15.0 | 3135 | 0.9448 | 0.2911 | 0.7418 | 0.1588 | 0.2924 | 0.0139 | -1.0 | 0.0241 | 0.1877 | 0.4678 | 0.4702 | 0.0122 | -1.0 | 0.2911 | 0.4678 | -1.0 | -1.0 |
| 0.9027 | 16.0 | 3344 | 0.9259 | 0.3033 | 0.7549 | 0.174 | 0.3047 | 0.005 | -1.0 | 0.0249 | 0.1931 | 0.4736 | 0.4762 | 0.0041 | -1.0 | 0.3033 | 0.4736 | -1.0 | -1.0 |
| 0.8725 | 17.0 | 3553 | 0.9200 | 0.3039 | 0.7554 | 0.1795 | 0.3055 | 0.0069 | -1.0 | 0.0259 | 0.1949 | 0.4764 | 0.479 | 0.0061 | -1.0 | 0.3039 | 0.4764 | -1.0 | -1.0 |
| 0.8725 | 18.0 | 3762 | 0.9129 | 0.3068 | 0.7622 | 0.1786 | 0.3083 | 0.0089 | -1.0 | 0.026 | 0.1961 | 0.4817 | 0.4842 | 0.0082 | -1.0 | 0.3068 | 0.4817 | -1.0 | -1.0 |
| 0.8725 | 19.0 | 3971 | 0.9053 | 0.3129 | 0.7699 | 0.182 | 0.3146 | 0.0119 | -1.0 | 0.0253 | 0.1986 | 0.4806 | 0.4832 | 0.0102 | -1.0 | 0.3129 | 0.4806 | -1.0 | -1.0 |
| 0.8532 | 20.0 | 4180 | 0.9124 | 0.3076 | 0.7661 | 0.1794 | 0.3093 | 0.0069 | -1.0 | 0.0252 | 0.1972 | 0.4798 | 0.4823 | 0.0061 | -1.0 | 0.3076 | 0.4798 | -1.0 | -1.0 |
| 0.8532 | 21.0 | 4389 | 0.9060 | 0.3129 | 0.7694 | 0.182 | 0.3146 | 0.0139 | -1.0 | 0.0254 | 0.1988 | 0.4811 | 0.4837 | 0.0122 | -1.0 | 0.3129 | 0.4811 | -1.0 | -1.0 |
| 0.8362 | 22.0 | 4598 | 0.9007 | 0.3157 | 0.7733 | 0.1886 | 0.3173 | 0.0079 | -1.0 | 0.0255 | 0.2005 | 0.4834 | 0.4859 | 0.0061 | -1.0 | 0.3157 | 0.4834 | -1.0 | -1.0 |
| 0.8362 | 23.0 | 4807 | 0.9036 | 0.3148 | 0.7702 | 0.1859 | 0.3159 | 0.0119 | -1.0 | 0.0255 | 0.1982 | 0.4859 | 0.4884 | 0.0102 | -1.0 | 0.3148 | 0.4859 | -1.0 | -1.0 |
| 0.8211 | 24.0 | 5016 | 0.8988 | 0.3159 | 0.7733 | 0.1875 | 0.3172 | 0.005 | -1.0 | 0.0253 | 0.1988 | 0.4844 | 0.487 | 0.0041 | -1.0 | 0.3159 | 0.4844 | -1.0 | -1.0 |
| 0.8211 | 25.0 | 5225 | 0.8989 | 0.3175 | 0.7741 | 0.1888 | 0.3189 | 0.0079 | -1.0 | 0.0256 | 0.1995 | 0.486 | 0.4886 | 0.0061 | -1.0 | 0.3175 | 0.486 | -1.0 | -1.0 |
| 0.8211 | 26.0 | 5434 | 0.8980 | 0.3188 | 0.776 | 0.1918 | 0.3204 | 0.005 | -1.0 | 0.0258 | 0.1998 | 0.4867 | 0.4893 | 0.0041 | -1.0 | 0.3188 | 0.4867 | -1.0 | -1.0 |
| 0.8091 | 27.0 | 5643 | 0.8953 | 0.3204 | 0.7786 | 0.1931 | 0.3219 | 0.0079 | -1.0 | 0.026 | 0.2002 | 0.4863 | 0.4889 | 0.0061 | -1.0 | 0.3204 | 0.4863 | -1.0 | -1.0 |
| 0.8091 | 28.0 | 5852 | 0.8973 | 0.3192 | 0.7784 | 0.1911 | 0.3208 | 0.0079 | -1.0 | 0.0255 | 0.199 | 0.4867 | 0.4892 | 0.0061 | -1.0 | 0.3192 | 0.4867 | -1.0 | -1.0 |
| 0.8001 | 29.0 | 6061 | 0.8962 | 0.3196 | 0.7785 | 0.1926 | 0.3211 | 0.0079 | -1.0 | 0.0257 | 0.1994 | 0.487 | 0.4896 | 0.0061 | -1.0 | 0.3196 | 0.487 | -1.0 | -1.0 |
| 0.8001 | 30.0 | 6270 | 0.8959 | 0.3195 | 0.7784 | 0.1925 | 0.3211 | 0.0079 | -1.0 | 0.0256 | 0.1995 | 0.487 | 0.4896 | 0.0061 | -1.0 | 0.3195 | 0.487 | -1.0 | -1.0 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
whizzzzkid/whizzzzkid_363_1 | whizzzzkid | 2024-07-01T09:08:03Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:06:36Z | Entry not found |
imcertibtw/cfwmagic | imcertibtw | 2024-07-01T09:08:21Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-01T09:07:16Z | ---
license: openrail
---
|
johnwee1/starcoder-1b-rust | johnwee1 | 2024-07-01T09:07:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_bigcode",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:07:28Z | ---
library_name: transformers
tags: []
---
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tanaymehta/gpt2_12H_12L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:07:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:07:43Z | ---
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tags: []
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tanaymehta/gpt2_12H_10L_1M_tok_50_eps | tanaymehta | 2024-07-01T09:08:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:07:56Z | ---
library_name: transformers
tags: []
---
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tanaymehta/gpt2_12H_12L_5M_tok_100_eps | tanaymehta | 2024-07-01T09:08:20Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:08:08Z | ---
library_name: transformers
tags: []
---
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tanaymehta/gpt2_12H_12L_10M_tok_100_eps | tanaymehta | 2024-07-01T09:08:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:08:22Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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imcertibtw/cfwtrick | imcertibtw | 2024-07-01T09:09:46Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-01T09:08:35Z | ---
license: openrail
---
|
DafangZhang/xijia | DafangZhang | 2024-07-01T09:08:45Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:08:45Z | Entry not found |
Jacie-Crown/Seq2seq_Model | Jacie-Crown | 2024-07-01T09:09:09Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:09:09Z | Entry not found |
onexxxxxx/Commonly_used_SD_Model | onexxxxxx | 2024-07-01T09:10:23Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:09:12Z | Entry not found |
suosuo123/large_dataset | suosuo123 | 2024-07-01T09:09:42Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:09:42Z | Entry not found |
imcertibtw/cfwjudge | imcertibtw | 2024-07-01T09:11:42Z | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | 2024-07-01T09:10:38Z | ---
license: openrail
---
|
Vincent-Ortiz-bis/my_awesome_model | Vincent-Ortiz-bis | 2024-07-01T09:13:38Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:13:38Z | Entry not found |
lwqkiller/sword001 | lwqkiller | 2024-07-01T09:14:01Z | 0 | 0 | null | [
"license:afl-3.0",
"region:us"
] | null | 2024-07-01T09:14:01Z | ---
license: afl-3.0
---
|
whizzzzkid/whizzzzkid_364_2 | whizzzzkid | 2024-07-01T09:20:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:18:46Z | Entry not found |
Arvind004/w2v-bert-2.0-mongolian-colab-CV16.0 | Arvind004 | 2024-07-01T09:19:56Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:19:55Z | ---
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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whizzzzkid/whizzzzkid_365_6 | whizzzzkid | 2024-07-01T09:22:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:21:28Z | Entry not found |
rristo/w2v-bert-2.0-mongolian-colab-CV16.0 | rristo | 2024-07-01T09:48:00Z | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:21:37Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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krittapol/Sandee2 | krittapol | 2024-07-01T09:34:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:22:34Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
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whizzzzkid/whizzzzkid_366_4 | whizzzzkid | 2024-07-01T09:25:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:23:54Z | Entry not found |
HikariLight/Mistral-7B-v0.2_SFT_Merged | HikariLight | 2024-07-01T09:27:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"trl",
"sft",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:24:29Z | ---
library_name: transformers
tags:
- trl
- sft
---
# Model Card for Model ID
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## Model Card Contact
[More Information Needed] |
whizzzzkid/whizzzzkid_367_5 | whizzzzkid | 2024-07-01T09:27:42Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:26:10Z | Entry not found |
tsc-data-science/outputs | tsc-data-science | 2024-07-02T02:29:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-07-01T09:27:46Z | ---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: outputs
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. -->
# outputs
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1489
- F1 Micro: 0.8209
- Precision Micro: 0.8209
- Recall Micro: 0.8209
## 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
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Precision Micro | Recall Micro |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:|
| 0.4507 | 0.7782 | 200 | 0.3227 | 0.0 | 0.0 | 0.0 |
| 0.263 | 1.5564 | 400 | 0.2081 | 0.5201 | 0.8744 | 0.3701 |
| 0.1789 | 2.3346 | 600 | 0.1686 | 0.7489 | 0.8231 | 0.6870 |
| 0.13 | 3.1128 | 800 | 0.1555 | 0.7691 | 0.8074 | 0.7343 |
| 0.1063 | 3.8911 | 1000 | 0.1416 | 0.7974 | 0.7649 | 0.8327 |
| 0.0844 | 4.6693 | 1200 | 0.1492 | 0.8 | 0.8008 | 0.7992 |
| 0.0617 | 5.4475 | 1400 | 0.1449 | 0.8268 | 0.8268 | 0.8268 |
| 0.0534 | 6.2257 | 1600 | 0.1388 | 0.8283 | 0.8258 | 0.8307 |
| 0.0352 | 7.0039 | 1800 | 0.1471 | 0.8272 | 0.8297 | 0.8248 |
| 0.0296 | 7.7821 | 2000 | 0.1489 | 0.8209 | 0.8209 | 0.8209 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.0.post100
- Datasets 2.19.0
- Tokenizers 0.19.1
|
styalai/XT-test-0.5 | styalai | 2024-07-01T10:03:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"pytorch_model_hub_mixin",
"model_hub_mixin",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:27:48Z | ---
tags:
- pytorch_model_hub_mixin
- model_hub_mixin
---
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
- Library: [More Information Needed]
- Docs: [More Information Needed] |
limaatulya/my_awesome_billsum_model_3 | limaatulya | 2024-07-01T09:28:01Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text2text-generation | 2024-07-01T09:27:53Z | ---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: my_awesome_billsum_model_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. -->
# my_awesome_billsum_model_3
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None 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: 2e-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
- num_epochs: 100
### Training results
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
humayunarain/results | humayunarain | 2024-07-01T09:28:58Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:28:58Z | Entry not found |
Artguy32/tPonynai3_v55-safetensors | Artguy32 | 2024-07-01T10:14:01Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:29:02Z | Entry not found |
JiaxinGe/llama3_bbh_data_anthropic_dataset_generated_dyck_1000 | JiaxinGe | 2024-07-01T09:31:52Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:31:45Z | ---
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
base_model: unsloth/llama-3-8b-bnb-4bit
---
# Uploaded model
- **Developed by:** JiaxinGe
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
carlosvillu/phi3-fine-tunning-test | carlosvillu | 2024-07-01T10:18:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"base_model:unsloth/phi-3-mini-4k-instruct-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:32:03Z | ---
base_model: unsloth/phi-3-mini-4k-instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
---
# Uploaded model
- **Developed by:** carlosvillu
- **License:** apache-2.0
- **Finetuned from model :** unsloth/phi-3-mini-4k-instruct-bnb-4bit
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
suosuo123/gorl | suosuo123 | 2024-07-01T09:35:12Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:32:18Z | Invalid username or password. |
thaisonatk/OpenELM | thaisonatk | 2024-07-03T01:26:49Z | 0 | 0 | null | [
"tensorboard",
"safetensors",
"region:us"
] | null | 2024-07-01T09:34:36Z | Entry not found |
kaitehtzeng/llama-3-youko-8b-tiny-tune | kaitehtzeng | 2024-07-01T09:47:34Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"llama",
"text-generation",
"unsloth",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T09:36:50Z | ---
library_name: transformers
tags:
- unsloth
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [More Information Needed]
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
[More Information Needed]
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
### 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] |
oleshy/ontochem_biobert-cross-valid-1 | oleshy | 2024-07-01T12:16:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | token-classification | 2024-07-01T09:36:56Z | ---
tags:
- generated_from_trainer
model-index:
- name: ontochem_biobert-cross-valid-1
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. -->
# ontochem_biobert-cross-valid-1
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0742
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 48 | 0.0672 |
| No log | 2.0 | 96 | 0.0677 |
| No log | 3.0 | 144 | 0.0678 |
| No log | 4.0 | 192 | 0.0735 |
| No log | 5.0 | 240 | 0.0742 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|
suosuo123/formix | suosuo123 | 2024-07-01T09:37:09Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:37:09Z | Entry not found |
manbeast3b/ZZZZZZZZdriver118 | manbeast3b | 2024-07-01T09:39:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T09:37:12Z | Entry not found |
humayunarain/test_trainer | humayunarain | 2024-07-01T09:37:17Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:37:17Z | Entry not found |
net31/naschainv42 | net31 | 2024-07-01T09:38:15Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:38:14Z | Entry not found |
Enno-Ai/EnnoAi-Pro-French-Llama-3-8B | Enno-Ai | 2024-07-02T09:52:06Z | 0 | 0 | null | [
"chatml",
"fr",
"en",
"license:creativeml-openrail-m",
"region:us"
] | null | 2024-07-01T09:38:50Z | ---
license: creativeml-openrail-m
language:
- fr
- en
tags:
- chatml
---
# French Pro model
Suitable model for professional use.
# Dataset
EnnoAi-Pro has been trained on a French dataset to enhance its analysis and response quality.
The dataset contains ~275K high-quality training samples of professional and general strategic themes.
# Tuning
Use specific receipices with QLora methods.
# Prompt Format
We use the default ChatML format with `system` role support.
```
<|begin_of_text|><|im_start|>system
{SYSTEM_CONTEXT}<|im_end|>
<|im_start|>user
{USER_ENTRY}<|im_end|>
<|im_start|>assistant
{ASSISTANT_ENTRY}<|im_end|>
```
**This model is under construction** |
kaya-kedi/OhLongJohnsonCat-TITANPretrain | kaya-kedi | 2024-07-01T09:41:45Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:40:19Z | Entry not found |
Nate344/whisper-small-hr | Nate344 | 2024-07-01T11:15:56Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T09:40:46Z | Entry not found |
anandohm/Ol-chiki_Santhali | anandohm | 2024-07-01T09:41:13Z | 0 | 0 | null | [
"license:unknown",
"region:us"
] | null | 2024-07-01T09:40:49Z | ---
license: unknown
---
|
limaatulya/my_awesome_billsum_model_4 | limaatulya | 2024-07-01T09:43:30Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text2text-generation | 2024-07-01T09:43:21Z | ---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: my_awesome_billsum_model_4
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. -->
# my_awesome_billsum_model_4
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None 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: 2e-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
- num_epochs: 100
### Training results
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|
syedmuhammad/UrduToBrailler_T5 | syedmuhammad | 2024-07-01T10:47:36Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:44:24Z | Entry not found |
eustlb/distil-large-v3-es | eustlb | 2024-07-01T10:31:23Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T09:46:15Z | Entry not found |
apwic/summarization-base-4 | apwic | 2024-07-01T13:04:12Z | 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 | 2024-07-01T09:46:18Z | ---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-base-4
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-4
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: 0.4923
- Rouge1: 0.3905
- Rouge2: 0.0
- Rougel: 0.3898
- Rougelsum: 0.3916
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.6327 | 1.0 | 3567 | 0.4634 | 0.3795 | 0.0 | 0.3806 | 0.3802 | 1.0 |
| 0.4349 | 2.0 | 7134 | 0.4541 | 0.3596 | 0.0 | 0.3615 | 0.3631 | 1.0 |
| 0.3376 | 3.0 | 10701 | 0.4562 | 0.4121 | 0.0 | 0.4123 | 0.4116 | 1.0 |
| 0.2683 | 4.0 | 14268 | 0.4744 | 0.3886 | 0.0 | 0.3869 | 0.388 | 1.0 |
| 0.2208 | 5.0 | 17835 | 0.4923 | 0.3905 | 0.0 | 0.3898 | 0.3916 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|
EnorSuarez/llamatunning | EnorSuarez | 2024-07-01T09:48:27Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:48:27Z | Entry not found |
VISHNUKUMAR001/meta-llama | VISHNUKUMAR001 | 2024-07-01T09:49:15Z | 0 | 0 | null | [
"license:llama3",
"region:us"
] | null | 2024-07-01T09:49:15Z | ---
license: llama3
---
|
lucasjin/mvbench_jsons_old | lucasjin | 2024-07-01T09:49:24Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:49:23Z | Entry not found |
Myriam123/tun_msa_wav2vec | Myriam123 | 2024-07-01T16:57:12Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2024-07-01T09:49:40Z | Entry not found |
Nangni/mistral_friends | Nangni | 2024-07-01T09:51:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T09:50:27Z | ---
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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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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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]
## Training Details
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## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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eros68/eros | eros68 | 2024-07-01T09:53:55Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:53:55Z | Entry not found |
psimoes/repmodel1 | psimoes | 2024-07-01T09:59:05Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T09:59:05Z | Entry not found |
pietrolesci/bert-civilcomments-gradtracking | pietrolesci | 2024-07-01T10:00:38Z | 0 | 0 | null | [
"tensorboard",
"region:us"
] | null | 2024-07-01T10:00:16Z | Entry not found |
zurd46/CodeGemma | zurd46 | 2024-07-01T10:32:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"gemma",
"trl",
"en",
"base_model:unsloth/gemma-7b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:02:20Z | ---
base_model: unsloth/gemma-7b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
---
# Uploaded model
- **Developed by:** zurd46
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-7b-bnb-4bit
This gemma 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)
|
manbeast3b/ZZZZZZZZdriver118c | manbeast3b | 2024-07-01T10:05:41Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T10:03:11Z | Entry not found |
Boostaro155/Nooro7888 | Boostaro155 | 2024-07-01T10:07:41Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:03:26Z | # [ALERT] Nooro Leg Massager Reviews Buy Now At Discount Experiences Official Price
[ALERT] Nooro Leg Massager Reviews – Nooro Foot Massager is an electrically-powered foot massager that targets special points - the acupuncture points - on your foot to relieve foot muscle fatigue and promote feet health. This state-of-the-art massage table is equivalent to a mini spa that works right out of the box to improve pedal blood circulation. Luckily you don't have to spend several dollars or your time in standard spas because Nooro Foot Massager provides at-home service.
## **[Click Here To Buy Now From Official Website Of Nooro Leg Massager](https://slim-gummies-deutschland.de/nooro-leg-massager)**
## Features and Benefits of Nooro Leg Massager
The Nooro Leg Massager is packed with features designed to provide a soothing and effective massage experience. With multiple intensity levels and massage modes, it caters to individual preferences for relaxation and muscle relief. The adjustable straps ensure a comfortable fit for various leg sizes, making it suitable for different users.
This innovative massager targets buzz befender pro reviews key pressure points in the legs, promoting better circulation and reducing stiffness. Its compact design allows for convenient use at home or on the go, making it a versatile wellness companion. The heat therapy function adds an extra layer of comfort by helping to alleviate tension in the muscles.
Whether you're looking to unwind after a long day or enhance your recovery post-workout, the Nooro Leg Massager offers a range of benefits that can support your overall well-being.
## Customer Reviews and Feedback
Customer reviews and feedback are crucial when considering purchasing a product like the Nooro Leg Massager. Many users have shared their experiences after using this device, highlighting various aspects of its performance. Some customers have praised the effectiveness of the massager in relieving muscle tension and improving circulation in their legs. They mentioned feeling more relaxed and rejuvenated after each session.
Others appreciated the customizable vitaletiks wrist sleeve reviews settings that allowed them to adjust intensity levels according to their preferences. A common theme among reviews is how convenient it is to use at home or even at work, making it a versatile option for busy individuals looking to incorporate self-care into their daily routine. Additionally, many users found the compact design and portability of the Nooro Leg Massager to be major selling points.
Customer feedback on the Nooro Leg Massager has been largely positive, with most users reporting satisfaction with its performance and benefits for leg relaxation and recovery.
## Comparison with Other Leg Massagers
When it comes to comparing the Nooro Leg Massager with other options on the market, there are a few key aspects to consider.
One important factor is the design and functionality of the massager. The Nooro Leg Massager is known for breath guard buddy reviews its innovative technology that targets multiple pressure points simultaneously, providing a comprehensive massage experience.
## **[Click Here To Buy Now From Official Website Of Nooro Leg Massager](https://slim-gummies-deutschland.de/nooro-leg-massager)** |
itay-nakash/model_5197e544a9_sweep_rose-water-1017 | itay-nakash | 2024-07-01T10:03:29Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:03:29Z | Entry not found |
1231czx/7b_dpo_iter2_4e7_onpolicy_only | 1231czx | 2024-07-01T10:11:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:03:52Z | ---
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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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]
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
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[More Information Needed]
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
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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]
- **Hours used:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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vowovow/repo_name | vowovow | 2024-07-01T10:04:23Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:04:23Z | Entry not found |
itay-nakash/model_8ef32107f0_sweep_deft-haze-1019 | itay-nakash | 2024-07-01T10:05:07Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:05:07Z | Entry not found |
bobtk/mlx-communityLlama-3-Swallow-70B-Instruct-v0.1-8bit | bobtk | 2024-07-01T10:07:36Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:07:36Z | Entry not found |
net31/naschainv39 | net31 | 2024-07-01T10:09:26Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:09:25Z | Entry not found |
itay-nakash/model_5197e544a9_sweep_pretty-meadow-1024 | itay-nakash | 2024-07-01T10:10:03Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:10:03Z | Entry not found |
habulaj/11113485922 | habulaj | 2024-07-01T10:11:06Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:11:02Z | Entry not found |
habulaj/201257174710 | habulaj | 2024-07-01T10:11:33Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:11:30Z | Entry not found |
avkr2502/Meta-Llama-3-8B-Instruct-Virtual-Recruiter-Finetuned | avkr2502 | 2024-07-01T10:17:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:16:05Z | ---
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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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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## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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LongshenOu/4-bar_inst-voice-control | LongshenOu | 2024-07-01T10:16:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:16:15Z | ---
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. -->
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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[More Information Needed]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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<!-- 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]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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<!-- 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
<!-- 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]
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|
sarath0098/flan-t5-xl | sarath0098 | 2024-07-01T10:16:17Z | 0 | 0 | null | [
"license:llama3",
"region:us"
] | null | 2024-07-01T10:16:17Z | ---
license: llama3
---
|
RedaAlami/falcon-11b-instruct-dpo-full | RedaAlami | 2024-07-01T10:16:46Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:16:46Z | Entry not found |
itay-nakash/model_788c2d3eed_sweep_vibrant-water-1025 | itay-nakash | 2024-07-01T10:16:48Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:16:47Z | Entry not found |
sarahai/whisper-large-uzbek | sarahai | 2024-07-01T10:17:39Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:17:39Z | Entry not found |
GraydientPlatformAPI/whitepony3 | GraydientPlatformAPI | 2024-07-01T10:39:27Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2024-07-01T10:18:10Z | Entry not found |
itay-nakash/model_7e21b47d14_sweep_vivid-mountain-1027 | itay-nakash | 2024-07-01T10:18:59Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:18:59Z | Entry not found |
ShapeKapseln33/G7PlusGreen65 | ShapeKapseln33 | 2024-07-01T10:21:57Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:19:45Z | G7 Green Gummies België Recensies De fruitgums bevatten een speciale G7 Plus formule. Volgens de fabrikant is het ontwikkeld door experts en bestaat het uit veel natuurlijke componenten. De Green Gummies zijn vegan en gelatinevrij. Dit betekent dat ze ook door vegetariërs en veganisten kunnen worden ingenomen.
**[Klik hier om nu te kopen via de officiële website van G7 Plus Green Gummies](https://adtocart.xyz/g7-green-gummies-be)**
##Een negatief punt over de G7 Plus Gummies?
Het beste aan G7 Green Gummies is dat ze geen negatieve effecten hebben, omdat ze volledig zijn gemaakt van natuurlijke ingrediënten die het lichaam nooit kunnen schaden. De negatieve effecten van G7-gummies voor gewichtsverlies zijn door veel mensen gemeld via positieve recensies en niemand heeft negatieve effecten gemeld, wat bewijst dat iedereen deze gummies kan proberen zonder zich zorgen te hoeven maken over de effecten. U hoeft slechts één ding in gedachten te houden: u moet het advies van uw arts raadplegen over de vraag of het geschikt is voor uw lichaam, anders krijgt u geen allergische reactie op een van de ingrediënten.
##Hoe gebruik je G7 Plus Gummies?
Het consumeren van deze gummies is heel eenvoudig omdat ze kauwbaar zijn en er geen specifieke tijd voor nodig is om ze te consumeren.
Een persoon zou een maand lang 2 gummies per dag moeten nemen, en ze worden geleverd in een verpakking van 60 gummies, dus één pakket is genoeg voor een maand. Als u wilt afvallen, mag u een maand lang geen dosis overslaan, omdat extra consumptie ook schadelijk is. Daarom wordt aanbevolen om de stappen die op de achterkant van de verpakking staan zorgvuldig te volgen.
##G7 Plus Gummies-recensies van klanten
##Sommige G7 Plus Sliming-klanten: -
Het product is goed en bevredigend; Het maakt gebruik van appelciderazijn dat helpt bij het verbranden van vet en door te sporten kunt u uw gewicht verminderen, omdat het verbranden van vet energie produceert, zodat de energie helpt bij onze training. “Workout.” Eet twee snoepjes per dag, want ze zijn het proberen waard.
Ik wilde dit product proberen en ik ben geen fan van capsules, maar toen ik zag dat ze in de vorm van kauwgom kwamen, kon ik het niet laten en bestelde ze. Deze mooie gummibeertjes in de vorm van een beer zijn erg lekker en gemakkelijk te kauwen. Met zulke krachtige ingrediënten zijn ze de prijs-kwaliteitverhouding waard en zijn ze een must-have.
Dit product is de beste manier om af te vallen. Ik nam ze om af te vallen, maar ze hielpen me niet alleen met afvallen, ze hielpen me ook met mijn angst en binnen een paar weken kon ik de veranderingen in mijn lichaam zien. Nu heb ik vertrouwen in mijn uiterlijk en ben ik trots op mezelf.
Ik gebruik deze gummies nu al een jaar en voor iemand die altijd haast heeft en een drukke agenda heeft, hoef ik geen goed dieet of lichaamsbeweging te volgen, maar dankzij deze gummies heb ik mijn klachten kunnen verminderen. calorie-inname en gewicht. Neem er zonder enige moeite twee per dag van en ze werken automatisch op je lichaam.
**[Klik hier om nu te kopen via de officiële website van G7 Plus Green Gummies](https://adtocart.xyz/g7-green-gummies-be)**
Voor een lui persoon zoals ik kan ik geen routine instellen om aan mijn lichaam te werken en ik ben zeker een dik persoon, maar ik kan gewoon niet sporten en wegblijven van eten. Toen hoorde ik over deze geweldige afslanksnoepjes die je kunnen helpen zonder enige moeite af te vallen. In eerste instantie geloofde ik niet in het bestaan van zoiets, maar toen begon ik het te nemen en merkte ik een verandering in mijn dieet en in mijn lichaam. Beetje bij beetje viel ik af en ook mijn winderigheid verdween. Ik ben dit product dankbaar voor het verbeteren van mijn leven.
##Waar kun je G7 Plus Gummies kopen in Duitsland, Oostenrijk?
Je kunt deze snoepjes eenvoudig online kopen via de originele website, omdat ze niet offline beschikbaar zijn en je daarom een bestelling moet plaatsen om ze te krijgen. En indien voorradig, heeft u uw bestelling binnen enkele werkdagen in huis. De afslankzwendel G7 Plus is voor veel mensen geen optie.
##Diploma
Samenvattend kunnen we zien dat G7 Plus Green Gummies Gewichtsverlies Sliming een gamechanger is; Met alle kunstmatige en namaakproducten op de markt die gewichtsverlies beloven, bewezen deze snoepjes dat iedereen ongelijk had door te laten zien dat je zonder het mengen van kunstmatige producten iets nuttigers en natuurlijkers kunt creëren dat iedereen kan gebruiken zonder dat je hoeft na te denken over de negatieve effecten. Ik heb er geen.
Als je het nog steeds niet gelooft, zullen de bovenstaande beoordelingen al je twijfels en zorgen wegnemen, omdat het echte beoordelingen van mensen zijn. Gummy-snoepjes bevorderen niet alleen gewichtsverlies en verminderen het verlangen, maar bevorderen ook de spijsvertering en verbeteren de stofwisseling van het lichaam. Bovendien hebben we ontdekt dat de natuurlijke ingrediënten voor iedereen veilig zijn.
**[Klik hier om nu te kopen via de officiële website van G7 Plus Green Gummies](https://adtocart.xyz/g7-green-gummies-be)**
|
GraydientPlatformAPI/ytpony3860 | GraydientPlatformAPI | 2024-07-01T10:39:55Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"autotrain_compatible",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2024-07-01T10:19:54Z | Entry not found |
HikariLight/Mistral-7B-v0.3_SFT_Merged | HikariLight | 2024-07-01T10:23:20Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"trl",
"sft",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:20:22Z | ---
library_name: transformers
tags:
- trl
- sft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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[More Information Needed]
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#### Speeds, Sizes, Times [optional]
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#### Summary
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## Environmental Impact
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- **Hardware Type:** [More Information Needed]
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chainup244/Qwen-Qwen1.5-0.5B-1719829311 | chainup244 | 2024-07-01T10:22:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:21:59Z | ---
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]
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- **Language(s) (NLP):** [More Information Needed]
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[More Information Needed]
### Out-of-Scope Use
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[More Information Needed]
## Bias, Risks, and Limitations
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[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
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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]
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## Technical Specifications [optional]
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[More Information Needed]
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Pranja/temp-gemma-7b-unsloth-merged | Pranja | 2024-07-01T10:27:30Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"gemma",
"text-generation",
"text-generation-inference",
"unsloth",
"trl",
"sft",
"en",
"base_model:unsloth/gemma-2b-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-generation | 2024-07-01T10:23:11Z | ---
base_model: unsloth/gemma-2b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
- sft
---
# Uploaded model
- **Developed by:** Pranja
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma 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)
|
mmolony/q-FrozenLake-v1-4x4-noSlippery | mmolony | 2024-07-01T10:23:35Z | 0 | 0 | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | 2024-07-01T10:23:33Z | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="mmolony/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
suminiui/chatfriends | suminiui | 2024-07-01T11:55:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:24:01Z | ---
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]
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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
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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#### Testing Data
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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]
- **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]
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[More Information Needed]
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y1xing/llama-3-8b-Instruct-bnb-4bit-learn-marking-synthetic-data-batch-size-2 | y1xing | 2024-07-01T10:25:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-Instruct-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:25:02Z | ---
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** y1xing
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
peft-internal-testing/DoRA-Hermes-2-Pro-Mistral-7B | peft-internal-testing | 2024-07-01T10:39:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:26:31Z | ---
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]
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ishmanish/opt-6.7b-loraHrPolicy | ishmanish | 2024-07-01T10:27:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:27:08Z | ---
library_name: transformers
tags: []
---
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chainup244/Qwen-Qwen1.5-1.8B-1719829653 | chainup244 | 2024-07-01T10:29:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | text-generation | 2024-07-01T10:27:36Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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Pranja/temp-gemma-7b-unsloth | Pranja | 2024-07-01T10:27:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"gemma",
"trl",
"en",
"base_model:unsloth/gemma-2b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:27:39Z | ---
base_model: unsloth/gemma-2b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- gemma
- trl
---
# Uploaded model
- **Developed by:** Pranja
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-2b-bnb-4bit
This gemma 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)
|
CennetOguz/cooking_blip2_30 | CennetOguz | 2024-07-01T10:28:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:28:26Z | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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ClementineBleuze/roberta_prefix_SEP | ClementineBleuze | 2024-07-01T12:21:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-07-01T10:28:56Z | ---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_prefix_SEP
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_prefix_SEP
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1216
- F1 Weighted: 0.8485
- F1 Samples: 0.8542
- F1 Macro: 0.7240
- F1 Micro: 0.8523
- Accuracy: 0.8268
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Weighted | F1 Samples | F1 Macro | F1 Micro | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:-----------:|:----------:|:--------:|:--------:|:--------:|
| 0.2716 | 0.3381 | 500 | 0.1879 | 0.7116 | 0.7074 | 0.3867 | 0.7460 | 0.6881 |
| 0.1741 | 0.6761 | 1000 | 0.1473 | 0.7886 | 0.7838 | 0.6033 | 0.8078 | 0.7632 |
| 0.1503 | 1.0142 | 1500 | 0.1379 | 0.7968 | 0.7917 | 0.6159 | 0.8111 | 0.7706 |
| 0.1309 | 1.3523 | 2000 | 0.1402 | 0.8034 | 0.7919 | 0.6646 | 0.8083 | 0.7686 |
| 0.1282 | 1.6903 | 2500 | 0.1324 | 0.8231 | 0.8207 | 0.6739 | 0.8271 | 0.7889 |
| 0.1242 | 2.0284 | 3000 | 0.1395 | 0.8151 | 0.8177 | 0.6768 | 0.8157 | 0.7855 |
| 0.1002 | 2.3665 | 3500 | 0.1277 | 0.8311 | 0.8310 | 0.6927 | 0.8367 | 0.8045 |
| 0.1002 | 2.7045 | 4000 | 0.1337 | 0.8182 | 0.8231 | 0.6556 | 0.8254 | 0.7977 |
| 0.1036 | 3.0426 | 4500 | 0.1319 | 0.8326 | 0.8343 | 0.6814 | 0.8347 | 0.8038 |
| 0.0851 | 3.3807 | 5000 | 0.1269 | 0.8316 | 0.8338 | 0.6857 | 0.8378 | 0.8078 |
| 0.0857 | 3.7187 | 5500 | 0.1210 | 0.8416 | 0.8453 | 0.6941 | 0.8454 | 0.8194 |
| 0.0818 | 4.0568 | 6000 | 0.1216 | 0.8485 | 0.8542 | 0.7240 | 0.8523 | 0.8268 |
| 0.0665 | 4.3949 | 6500 | 0.1347 | 0.8374 | 0.8445 | 0.7160 | 0.8420 | 0.8200 |
| 0.0683 | 4.7329 | 7000 | 0.1281 | 0.8440 | 0.8505 | 0.7119 | 0.8485 | 0.8234 |
| 0.0641 | 5.0710 | 7500 | 0.1344 | 0.8387 | 0.8446 | 0.6990 | 0.8410 | 0.8139 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|
sivakarri/roberta_nba_flash_v2 | sivakarri | 2024-07-01T10:51:53Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | text-classification | 2024-07-01T10:28:58Z | Entry not found |
kr-manish/opt-6.7b-loraHrPolicy | kr-manish | 2024-07-01T10:29:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-07-01T10:29:27Z | ---
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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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
#### Testing Data
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<!-- Relevant interpretability work for the model goes here -->
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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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hungkvbn/naschainv6 | hungkvbn | 2024-07-01T10:29:29Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:29:27Z | Entry not found |
net31/naschainv24 | net31 | 2024-07-01T16:56:27Z | 0 | 0 | null | [
"region:us"
] | null | 2024-07-01T10:30:18Z | Entry not found |
mmolony/Taxi-v3 | mmolony | 2024-07-01T10:30:51Z | 0 | 0 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | reinforcement-learning | 2024-07-01T10:30:49Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.52 +/- 2.71
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="mmolony/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
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