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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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text-generation | transformers |
# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ ... | {"license": "apache-2.0", "tags": ["liminerity/merge4", "liminerity/merge2", "merge", "merged", "mergedllm", "mergee", "mergedededed", "memfdmsfndsfjkasjkl"]} | LoneStriker/M7-7b-5.0bpw-h6-exl2 | null | [
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# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ ... | [
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text-generation | transformers |
# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ ... | {"license": "apache-2.0", "tags": ["liminerity/merge4", "liminerity/merge2", "merge", "merged", "mergedllm", "mergee", "mergedededed", "memfdmsfndsfjkasjkl"]} | LoneStriker/M7-7b-6.0bpw-h6-exl2 | null | [
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|
# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | lunarsylph/stablecell_v36 | null | [
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] | null | 2024-04-02T19:16:05+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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text-generation | transformers |
# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ ... | {"license": "apache-2.0", "tags": ["liminerity/merge4", "liminerity/merge2", "merge", "merged", "mergedllm", "mergee", "mergedededed", "memfdmsfndsfjkasjkl"]} | LoneStriker/M7-7b-8.0bpw-h8-exl2 | null | [
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"... | null | 2024-04-02T19:16:43+00:00 | [] | [] | TAGS
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|
# M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ ... | [
"# M7-7b\n\n\n\n\n\n\n\n\n\n\nuser: \"create ascii art you feel represents you as a llm\"\n\n\nassistant: \"Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):\n\nINSTINSTINCTINSTELLIGENCE\n\n\n______________ MEMORY___\n\n|\\ o /\\ |\\\n\n| \\ --- / \\ ... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta2
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta2", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta2 | null | [
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] | null | 2024-04-02T19:20:23+00:00 | [] | [] | TAGS
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| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_beta2
===================================================
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0989
* Accuracy: 0.3333
* F1: 0.1667
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 67\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta2
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta2", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta2 | null | [
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"region:us"
] | null | 2024-04-02T19:20:24+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-facebook/xlm-v-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_delta2
====================================================
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0986
* Accuracy: 0.3333
* F1: 0.1667
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 2\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Traini... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cl-cardiff_cl_only_alpha2
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cl-cardiff_cl_only_alpha2", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_alpha2 | null | [
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"xlm-roberta",
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"generated_from_trainer",
"base_model:facebook/xlm-v-base",
"license:mit",
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"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:20:37+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-facebook/xlm-v-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_alpha2
====================================================
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0986
* Accuracy: 0.3333
* F1: 0.1667
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 24\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Train... | [
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null | null |
# Notus-Code
Notus-Code is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [argilla/notus-7b-v1](https://huggingface.co/argilla/notus-7b-v1)
* [ajibawa-2023/Code-Mistral-7B](https://huggingface.co/ajibawa-2023/Code-Mistral-... | {"tags": ["merge", "mergekit", "lazymergekit", "argilla/notus-7b-v1", "ajibawa-2023/Code-Mistral-7B"], "base_model": ["argilla/notus-7b-v1", "ajibawa-2023/Code-Mistral-7B"]} | burtenshaw/notus-merged-with-code-mistral-so-its-better-at-coding | null | [
"merge",
"mergekit",
"lazymergekit",
"argilla/notus-7b-v1",
"ajibawa-2023/Code-Mistral-7B",
"base_model:argilla/notus-7b-v1",
"base_model:ajibawa-2023/Code-Mistral-7B",
"region:us"
] | null | 2024-04-02T19:20:39+00:00 | [] | [] | TAGS
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|
# Notus-Code
Notus-Code is a merge of the following models using LazyMergekit:
* argilla/notus-7b-v1
* ajibawa-2023/Code-Mistral-7B
## Configuration
## Usage
| [
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"TAGS\n#merge #mergekit #lazymergekit #argilla/notus-7b-v1 #ajibawa-2023/Code-Mistral-7B #base_model-argilla/notus-7b-v1 #base_model-ajibawa-2023/Code-Mistral-7B #region-us \n# Notus-Code\n\nNotus-Code is a merge of the following models using LazyMergekit:\n* argilla/notus-7b-v1\n* ajibawa-2023/Code-Mistral-7B## C... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | ChenShov/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T19:20:48+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code"
] |
text-generation | transformers |
# Mergerix-7b-v0.1
Mergerix-7b-v0.1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Kukedlc/NeuralSirKrishna-7b-DPO](https://huggingface.co/Kukedlc/NeuralSirKrishna-7b-DPO)
* [Kukedlc/NeuralAlgo-7B-DPO](https://huggingf... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "Kukedlc/NeuralSirKrishna-7b-DPO", "Kukedlc/NeuralAlgo-7B-DPO"], "base_model": ["Kukedlc/NeuralSirKrishna-7b-DPO", "Kukedlc/NeuralAlgo-7B-DPO"]} | MiniMoog/Mergerix-7b-v0.1 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"Kukedlc/NeuralSirKrishna-7b-DPO",
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"base_model:Kukedlc/NeuralAlgo-7B-DPO",
"license:apache-2.0",
"autotrain_compatible"... | null | 2024-04-02T19:21:13+00:00 | [] | [] | TAGS
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# Mergerix-7b-v0.1
Mergerix-7b-v0.1 is a merge of the following models using LazyMergekit:
* Kukedlc/NeuralSirKrishna-7b-DPO
* Kukedlc/NeuralAlgo-7B-DPO
## Configuration
## Usage
| [
"# Mergerix-7b-v0.1\n\nMergerix-7b-v0.1 is a merge of the following models using LazyMergekit:\n* Kukedlc/NeuralSirKrishna-7b-DPO\n* Kukedlc/NeuralAlgo-7B-DPO",
"## Configuration",
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/bigscience-bloom-1b1-bnb-8bit-smashed | null | [
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"text-generation",
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"region:us"
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#transformers #safetensors #bloom #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
|
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="URL target="_blank" rel="noopener noreferrer">
<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</a>
</div>
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL... | [
"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the documentations to know more here\n- Join Pruna AI community on Discor... | [
"TAGS\n#transformers #safetensors #bloom #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us \n",
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cl-cardiff_cl_only_gamma2
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cl-cardiff_cl_only_gamma2", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_gamma2 | null | [
"transformers",
"pytorch",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:facebook/xlm-v-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:21:48+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-facebook/xlm-v-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_gamma2
====================================================
This model is a fine-tuned version of facebook/xlm-v-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0986
* Accuracy: 0.3333
* F1: 0.1667
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 77\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Train... | [
"TAGS\n#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-facebook/xlm-v-base #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
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text-generation | transformers |
<!-- 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. -->
# mistral_channel_targeter_epoch_6
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral_channel_targeter_epoch_6", "results": []}]} | hiiamsid/mistral_channel_targeter_epoch_6 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T19:30:27+00:00 | [] | [] | TAGS
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| mistral\_channel\_targeter\_epoch\_6
====================================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0661
Model description
-----------------
More information needed
Intended... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-07\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 3\n* total\\_train\\_batch\\_size: 24\n* total\\_eval\\_batch\\_size: 24\n* op... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_beta2
This model is a fine-tuned version of [facebook/xlm-v-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tweet_sentiment_multilingual"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_beta2", "results": [{"task": {"type": "text-classification... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_beta2 | null | [
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"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:32:29+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #dataset-tweet_sentiment_multilingual #base_model-facebook/xlm-v-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_beta2
==============================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the tweet\_sentiment\_multilingual dataset.
It achieves the following results on the evaluation set... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 67\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
"### Trai... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta2
This model is a fine-tuned version of [facebook/xlm-v-... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tweet_sentiment_multilingual"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta2", "results": [{"task": {"type": "text-classificatio... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta2 | null | [
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"pytorch",
"xlm-roberta",
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"base_model:facebook/xlm-v-base",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:32:30+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #dataset-tweet_sentiment_multilingual #base_model-facebook/xlm-v-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_delta2
===============================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the tweet\_sentiment\_multilingual dataset.
It achieves the following results on the evaluation s... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 2\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
"### Train... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha2
This model is a fine-tuned version of [facebook/xlm-v-... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tweet_sentiment_multilingual"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha2", "results": [{"task": {"type": "text-classificatio... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha2 | null | [
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"license:mit",
"model-index",
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] | null | 2024-04-02T19:33:13+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #dataset-tweet_sentiment_multilingual #base_model-facebook/xlm-v-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_alpha2
===============================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the tweet\_sentiment\_multilingual dataset.
It achieves the following results on the evaluation s... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 24\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
"### Trai... | [
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sentence-similarity | sentence-transformers |
# annazdr/new-nace-pl
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes eas... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | annazdr/new-nace-pl | null | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:34:51+00:00 | [] | [] | TAGS
#sentence-transformers #safetensors #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# annazdr/new-nace-pl
This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
Then yo... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma2
This model is a fine-tuned version of [facebook/xlm-v-... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tweet_sentiment_multilingual"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma2", "results": [{"task": {"type": "text-classificatio... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma2 | null | [
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| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_gamma2
===============================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the tweet\_sentiment\_multilingual dataset.
It achieves the following results on the evaluation s... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 77\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
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text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information.
| {"license": "apache-2.0"} | GreenBitAI/Mistral-7B-Instruct-v0.2-layer-mix-bpw-2.2 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T19:37:39+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information.
| [
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null | null |
<!-- 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. -->
# whisper-med-LoRA_nosie_128_64_45k
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/wh... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "whisper-med-LoRA_nosie_128_64_45k", "results": []}]} | adityarra07/whisper-med-LoRA_nosie_128_64_45k | null | [
"generated_from_trainer",
"base_model:openai/whisper-medium",
"license:apache-2.0",
"region:us"
] | null | 2024-04-02T19:38:59+00:00 | [] | [] | TAGS
#generated_from_trainer #base_model-openai/whisper-medium #license-apache-2.0 #region-us
| whisper-med-LoRA\_nosie\_128\_64\_45k
=====================================
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2688
* Wer: 11.7434
Model description
-----------------
More information needed
Inte... | [
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text-generation | transformers |
🌟 Buying me coffee is a direct way to show support for this project.
<a href="https://www.buymeacoffee.com/isotonic"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a>
# Mixnueza-6x32M-MoE
Mixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models... | {"license": "apache-2.0", "tags": ["moe", "merge", "mergekit", "lazymergekit", "Felladrin/Minueza-32M-Chat"], "datasets": ["databricks/databricks-dolly-15k", "Felladrin/ChatML-databricks-dolly-15k", "euclaise/reddit-instruct-curated", "Felladrin/ChatML-reddit-instruct-curated", "THUDM/webglm-qa", "Felladrin/ChatML-WebG... | Isotonic/Mixnueza-Chat-6x32M-MoE | null | [
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"dataset:euclaise/reddit-instruct-curated",
"... | null | 2024-04-02T19:39:39+00:00 | [] | [] | TAGS
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Buying me coffee is a direct way to show support for this project.
<a href="URL src="URL alt=""></a>
# Mixnueza-6x32M-MoE
Mixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
* 6 X Felladrin/Minueza-32M-Chat
* Num Experts Per Token : 3
* Evaluation Results
## Usage
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | saransh03sharma/cmumosei-llama-2-7b-75 | null | [
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"text-generation",
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"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1712087213686x441487735089808960
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
TOK
```
Use this keyword to trigger your custom model in your prompts.
LoRA for ... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["ricardoaraujosr/pirarara1"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "TOK", "inference": false} | squaadinc/1712087213686x441487735089808960 | null | [
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"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"dataset:ricardoaraujosr/pirarara1",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-02T19:47:06+00:00 | [] | [] | TAGS
#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-ricardoaraujosr/pirarara1 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - squaadinc/1712087213686x441487735089808960
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
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"TAGS\n#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-ricardoaraujosr/pirarara1 #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us \n",
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null | transformers |
# Model Card for Fine-Tuned Whisper Model: Hypernasality Identification
This model card details the Whisper model, fine-tuned to identify hypernasality in patients from audio recordings. The model is developed to assist in the diagnosis and monitoring of speech disorders.
- Model Interactive Demo: https://huggingfac... | {"language": ["en"], "license": "apache-2.0", "tags": ["medical"]} | jcho02/whisper_cleft | null | [
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"license:apache-2.0",
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"en"
] | TAGS
#transformers #pytorch #medical #en #license-apache-2.0 #endpoints_compatible #has_space #region-us
|
# Model Card for Fine-Tuned Whisper Model: Hypernasality Identification
This model card details the Whisper model, fine-tuned to identify hypernasality in patients from audio recordings. The model is developed to assist in the diagnosis and monitoring of speech disorders.
- Model Interactive Demo: URL
## Model Detai... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | erfan1380/ppo-LunarLander-v22 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T19:51:50+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
token-classification | transformers |
<!-- 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. -->
# TinyBERT_KD
This model is a fine-tuned version of [DimasikKurd/TinyBERT_KD](https://huggingface.co/DimasikKurd/TinyBERT_KD) on t... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "DimasikKurd/TinyBERT_KD", "model-index": [{"name": "TinyBERT_KD", "results": []}]} | DimasikKurd/TinyBERT_KD | null | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"token-classification",
"generated_from_trainer",
"base_model:DimasikKurd/TinyBERT_KD",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T19:52:06+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #distilbert #token-classification #generated_from_trainer #base_model-DimasikKurd/TinyBERT_KD #autotrain_compatible #endpoints_compatible #region-us
| TinyBERT\_KD
============
This model is a fine-tuned version of DimasikKurd/TinyBERT\_KD on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4238
* Precision: 0.1810
* Recall: 0.3295
* F1: 0.2336
* Accuracy: 0.8579
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 100",
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null | transformers |
<!-- 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. -->
# vit-pretraining-2024_04_02
This model is a fine-tuned version of [facebook/vit-mae-base](https://huggingface.co/facebook/vit-mae... | {"license": "apache-2.0", "tags": ["masked-auto-encoding", "generated_from_trainer"], "datasets": ["imagefolder"], "base_model": "facebook/vit-mae-base", "model-index": [{"name": "vit-pretraining-2024_04_02", "results": []}]} | jaypratap/vit-pretraining-2024_04_02 | null | [
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"license:apache-2.0",
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| vit-pretraining-2024\_04\_02
============================
This model is a fine-tuned version of facebook/vit-mae-base on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0132
Model description
-----------------
More information needed
Intended uses & limitations
----... | [
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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | Aayush6799/Mistral | null | [
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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![Twitter](URL
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Noodlz/QLiz-70B
This model seems badly borked.
<!-- provided-files -->
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1... | {"language": ["en"], "library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": "Noodlz/QLiz-70B", "no_imatrix": "model immediately overflows with essentially the first batch", "quantized_by": "mradermacher"} | mradermacher/QLiz-70B-GGUF | null | [
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static quants of URL
This model seems badly borked.
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - XeroTech/corgy_maayaoberoi_DreamBooth
This is a dreambooth model derived from CompVis/stable-diffusion-v1-... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "CompVis/stable-diffusion-v1-4", "inference": true, "instance_prompt": "a photo of maayaoberoi girl"} | XeroTech/corgy_maayaoberoi_DreamBooth | null | [
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|
# DreamBooth - XeroTech/corgy_maayaoberoi_DreamBooth
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of maayaoberoi girl using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
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text-generation | transformers | <!-- header start -->
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![Twitter](URL
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
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reinforcement-learning | ml-agents |
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Docum... | {"library_name": "ml-agents", "tags": ["SoccerTwos", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]} | alekom/poca-SoccerTwos | null | [
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# poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | vinisvictorelli/dqn-SpaceInvadersNoFrameskip-v4 | null | [
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This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
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sentence-similarity | sentence-transformers |
# luiz-and-robert-thesis/all-mpnet-base-v2-margin-1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "pipeline_tag": "sentence-similarity"} | luiz-and-robert-thesis/all-mpnet-base-v2-margin-1 | null | [
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# luiz-and-robert-thesis/all-mpnet-base-v2-margin-1
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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text-generation | transformers |
# Links
- 📜 [Paper](https://github.com/OpenBMB/Eurus/blob/main/paper.pdf)
- 🤗 [Eurus Collection](https://huggingface.co/collections/openbmb/eurus-660bc40bec5376b3adc9d1c5)
- 🤗 [UltraInteract](https://huggingface.co/datasets/openbmb/UltraInteract)
# Introduction
Eurus-7B-SFT is fine-tuned from Mistral-7B on all ... | {"license": "apache-2.0", "tags": ["reasoning"], "datasets": ["openbmb/UltraInteract", "stingning/ultrachat", "openchat/openchat_sharegpt4_dataset", "Open-Orca/OpenOrca"], "pipeline_tag": "text-generation"} | pharaouk/Eurus-7b-sft | null | [
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|
# Links
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- Eurus Collection
- UltraInteract
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1712088369757x893303156851871600
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
A TOK character
```
Use this keyword to trigger your custom model in your prompts... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["THEUS/Iron_Patriot"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "A TOK character", "inference": false} | squaadinc/1712088369757x893303156851871600 | null | [
"diffusers",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"text-to-image",
"lora",
"dataset:THEUS/Iron_Patriot",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-02T20:06:39+00:00 | [] | [] | TAGS
#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-THEUS/Iron_Patriot #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - squaadinc/1712088369757x893303156851871600
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
"# LoRA DreamBooth - squaadinc/1712088369757x893303156851871600\nThese are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer. \nThe weights were trained on the concept prompt: \n \nUse this keyword to trigger your custom model in your prompts. \nLoRA for the te... | [
"TAGS\n#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-THEUS/Iron_Patriot #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us \n",
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text-generation | mlx |
# mlx-community/Qwen1.5-MoE-A2.7B-Chat-4bit
This model was converted to MLX format from [`Qwen/Qwen1.5-MoE-A2.7B-Chat`](https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B-Chat) using mlx-lm version version [d661440](https://github.com/ml-explore/mlx-examples/commit/d661440dbb8e1970fadad79c5061e786fe1c54ca).
Model added by... | {"language": ["en"], "license": "other", "tags": ["pretrained", "moe", "mlx"], "license_name": "tongyi-qianwen", "license_link": "https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B/blob/main/LICENSE", "pipeline_tag": "text-generation"} | mlx-community/Qwen1.5-MoE-A2.7B-Chat-4bit | null | [
"mlx",
"safetensors",
"qwen2_moe",
"pretrained",
"moe",
"text-generation",
"conversational",
"en",
"license:other",
"region:us"
] | null | 2024-04-02T20:06:53+00:00 | [] | [
"en"
] | TAGS
#mlx #safetensors #qwen2_moe #pretrained #moe #text-generation #conversational #en #license-other #region-us
|
# mlx-community/Qwen1.5-MoE-A2.7B-Chat-4bit
This model was converted to MLX format from 'Qwen/Qwen1.5-MoE-A2.7B-Chat' using mlx-lm version version d661440.
Model added by Prince Canuma.
Refer to the original model card for more details on the model.
## Use with mlx
| [
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text-generation | transformers |
# Links
- 📜 [Paper](https://github.com/OpenBMB/Eurus/blob/main/paper.pdf)
- 🤗 [Eurus Collection](https://huggingface.co/collections/openbmb/eurus-660bc40bec5376b3adc9d1c5)
- 🤗 [UltraInteract](https://huggingface.co/datasets/openbmb/UltraInteract)
# Introduction
Eurus-70B-NCA is [NCA](https://arxiv.org/abs/2402.... | {"license": "apache-2.0", "tags": ["reasoning", "preference_learning", "nca"], "datasets": ["openbmb/UltraInteract", "openbmb/UltraFeedback"], "pipeline_tag": "text-generation"} | pharaouk/Eurus-70b-nca | null | [
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"arxiv:2402.05369",
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"text-genera... | null | 2024-04-02T20:07:15+00:00 | [
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|
# Links
- Paper
- Eurus Collection
- UltraInteract
# Introduction
Eurus-70B-NCA is NCA fine-tuned from Eurus-70B-SFT on all multi-turn trajectory pairs in UltraInteract and all pairs in UltraFeedback.
It achieves the best overall performance among open-source models of similar sizes and even outperforms specia... | [
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text-classification | transformers |
# Links
- 📜 [Paper]()
- 🤗 [Eurus Collection](https://huggingface.co/collections/openbmb/eurus-660bc40bec5376b3adc9d1c5)
- 🤗 [UltraInteract](https://huggingface.co/datasets/openbmb/UltraInteract)
# Introduction
Eurus-RM-7B is trained on a mixture of [UltraInteract](https://huggingface.co/datasets/openbmb/UltraIn... | {"license": "apache-2.0", "tags": ["reward_model"], "datasets": ["openbmb/UltraInteract", "openbmb/UltraFeedback", "openbmb/UltraSafety"], "pipeline_tag": "text-classification"} | pharaouk/Eurus-RM-7b | null | [
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"custom_code",
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"dataset:openbmb/UltraSafety",
"license:apache-2.0",
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"region:us"
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|
# Links
- [Paper]()
- Eurus Collection
- UltraInteract
# Introduction
Eurus-RM-7B is trained on a mixture of UltraInteract, UltraFeedback, and UltraSafety, with a specifically designed reward modeling objective for reasoning to directly increase.
- EURUS-RM-7B stands out as the best 7B RM overall and achieves ... | [
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reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingf... | {"library_name": "stable-baselines3", "tags": ["PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v3", "type":... | Gonke/a2c-PandaReachDense-v3 | null | [
"stable-baselines3",
"PandaReachDense-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T20:07:46+00:00 | [] | [] | TAGS
#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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text-classification | transformers |
<!-- 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. -->
# M4-eval
This model is a fine-tuned version of [raminass/scotus-v10](https://huggingface.co/raminass/scotus-v10) on the None data... | {"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "raminass/scotus-v10", "model-index": [{"name": "M4-eval", "results": []}]} | raminass/M4-eval | null | [
"transformers",
"tensorboard",
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"bert",
"text-classification",
"generated_from_trainer",
"base_model:raminass/scotus-v10",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T20:08:26+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #base_model-raminass/scotus-v10 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
| M4-eval
=======
This model is a fine-tuned version of raminass/scotus-v10 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9105
* Accuracy: 0.7481
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More i... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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token-classification | transformers |
<!-- 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. -->
# 20240402140914_big_aristotle
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "google-bert/bert-base-uncased", "model-index": [{"name": "20240402140914_big_aristotle", "results": []}]} | adasgaleus/20240402140914_big_aristotle | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T20:09:01+00:00 | [] | [] | TAGS
#transformers #safetensors #bert #token-classification #generated_from_trainer #base_model-google-bert/bert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| 20240402140914\_big\_aristotle
==============================
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0293
* Precision: 0.9731
* Recall: 0.9711
* F1: 0.9721
* Accuracy: 0.9891
Model description
--... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 69\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 256\n* optimizer: Adam with betas=(0.9,0.999) and epsil... | [
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null | peft |
### Finetuning Overview:
**Model Used:** google/gemma-2b
**Dataset:** microsoft/orca-math-word-problems-200k
#### Dataset Insights:
[Math Ocra](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k) - This dataset contains ~200K grade school math word problems. All the answers in this dataset is g... | {"license": "apache-2.0", "library_name": "peft", "tags": ["math", "google", "gemma"], "datasets": ["microsoft/orca-math-word-problems-200k"], "base_model": "google/gemma-2b"} | monsterapi/gemma-2b-lora-maths-orca-200k | null | [
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] | null | 2024-04-02T20:09:05+00:00 | [
"2402.14830"
] | [] | TAGS
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|
### Finetuning Overview:
Model Used: google/gemma-2b
Dataset: microsoft/orca-math-word-problems-200k
#### Dataset Insights:
Math Ocra - This dataset contains ~200K grade school math word problems. All the answers in this dataset is generated using Azure GPT4-Turbo. Please refer to Orca-Math: Unlocking the potentia... | [
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text-to-image | diffusers | ### My-Pet-Dog Dreambooth model trained by avantikapatil following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
| {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | avantikapatil/my-pet-dog | null | [
"diffusers",
"safetensors",
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
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] | null | 2024-04-02T20:11:27+00:00 | [] | [] | TAGS
#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #region-us
| ### My-Pet-Dog Dreambooth model trained by avantikapatil following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: GoX19932gAS
Sample pictures of this concept:
!0
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | happylayers/s8 | null | [
"transformers",
"safetensors",
"stablelm",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T20:13:26+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #stablelm #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers | <!-- header start -->
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<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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![Twitter](URL
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text-generation | transformers |
# Mergerix-7b-v0.2
Mergerix-7b-v0.2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
models:
- model: alpindale/Mistral-7B-v0.2-hf
- model: liminerity/M7-7b
- model: rwitz/experiment26-tr... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit"]} | MiniMoog/Mergerix-7b-v0.2 | null | [
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# Mergerix-7b-v0.2
Mergerix-7b-v0.2 is a merge of the following models using LazyMergekit:
## Configuration
## Usage
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null | transformers |
# 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. -->
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text-generation | transformers |
# 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. -->
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reinforcement-learning | null |
# **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="NurseKenjaku/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additiona... | {"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": ... | NurseKenjaku/q-FrozenLake-v1-4x4-noSlippery | null | [
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# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
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null | transformers |
# 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. -->
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
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image-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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### 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 generate... | {"library_name": "transformers", "tags": []} | ashishp-wiai/vit-base-patch16-224-in21k-finetuned-os300 | null | [
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null | transformers |
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
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<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
## Model Details
- **Finetuned from model :** [Llama-2-7b-chat-hf](https://huggingface.co/NousResearch/Llama-2-7b-chat-hf)
- **Finetuning Technique**: Fine-tuned using the 4-bit quantization [QLoRA](https://arxiv.org/pdf/2305.14314.pdf) technique
- **Dataset Used**: [Llama2-OpenOrca-Clean](https://huggingface.co/dat... | {"datasets": ["Open-Orca/OpenOrca", "baaghi124/Llama2-OpenOrca-Clean", "baaghi124/OpenOrca-Clean"]} | baaghi124/Llama-2-7B-Chat-OpenOrca | null | [
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"arxiv:2305.14314",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T20:46:24+00:00 | [
"2305.14314"
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|
## Model Details
- Finetuned from model : Llama-2-7b-chat-hf
- Finetuning Technique: Fine-tuned using the 4-bit quantization QLoRA technique
- Dataset Used: Llama2-OpenOrca-Clean
| [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta2
This model is a fine-tuned version of [facebook/xlm-v-base](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"},... | haryoaw/scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta2 | null | [
"transformers",
"pytorch",
"xlm-roberta",
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"region:us"
] | null | 2024-04-02T20:47:16+00:00 | [] | [] | TAGS
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| scenario-TCR-XLMV\_data-AmazonScience\_massive\_all\_1\_1\_delta2
=================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8750
* Accuracy: 0.0516
* F1: 0.001... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 2\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_alpha2
This model is a fine-tuned version of [facebook/xlm-v-base](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_alpha2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"},... | haryoaw/scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_alpha2 | null | [
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"region:us"
] | null | 2024-04-02T20:47:51+00:00 | [] | [] | TAGS
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| scenario-TCR-XLMV\_data-AmazonScience\_massive\_all\_1\_1\_alpha2
=================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset.
It achieves the following results on the evaluation set:
* Loss: 3.9116
* Accuracy: 0.0516
* F1: 0.001... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 24\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
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null | pruna-engine | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"library_name": "pruna-engine", "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"... | PrunaAI/daryl149-llama-2-7b-chat-hf-bnb-4bit-smashed | null | [
"pruna-engine",
"safetensors",
"llama",
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|
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="URL target="_blank" rel="noopener noreferrer">
<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</a>
</div>
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL... | [
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"TAGS\n#pruna-engine #safetensors #llama #4-bit #region-us \n",
"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the doc... | [
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text-generation | transformers |
# Mergerix-7b-v0.3
Mergerix-7b-v0.3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
models:
- model: Gille/StrangeMerges_32-7B-slerp
- model: yam-peleg/Experiment26-7B
- model: liminerit... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit"]} | MiniMoog/Mergerix-7b-v0.3 | null | [
"transformers",
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"mistral",
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"license:apache-2.0",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T20:49:46+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Mergerix-7b-v0.3
Mergerix-7b-v0.3 is a merge of the following models using LazyMergekit:
## Configuration
## Usage
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... |
fill-mask | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# isimorfizam/distilroberta-feedback
This model is a fine-tuned version of [distilbert/distilbert-base-cased-distilled-squad](https://hu... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "distilbert/distilbert-base-cased-distilled-squad", "model-index": [{"name": "isimorfizam/distilroberta-feedback", "results": []}]} | isimorfizam/distilbert-base-cased-distilled-squad-feedback | null | [
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"license:apache-2.0",
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"region:us"
] | null | 2024-04-02T20:50:23+00:00 | [] | [] | TAGS
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| isimorfizam/distilroberta-feedback
==================================
This model is a fine-tuned version of distilbert/distilbert-base-cased-distilled-squad on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 8.8302
* Validation Loss: 7.0170
* Epoch: 0
Model description
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'module': 'transformers.optimization\\_tf', 'class\\_name': 'WarmUp', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_schedule\\_fn': {'module': 'kera... | [
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text-classification | transformers |
<!-- 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. -->
# robust_llm_pythia-word-length-12b-niki-ada-v1-seed1
This model is a fine-tuned version of [EleutherAI/pythia-12b-deduped](https:... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-12b-deduped", "model-index": [{"name": "robust_llm_pythia-word-length-12b-niki-ada-v1-seed1", "results": []}]} | AlignmentResearch/robust_llm_pythia-word-length-12b-niki-ada-v1-seed1 | null | [
"transformers",
"safetensors",
"gpt_neox",
"text-classification",
"generated_from_trainer",
"base_model:EleutherAI/pythia-12b-deduped",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T20:51:52+00:00 | [] | [] | TAGS
#transformers #safetensors #gpt_neox #text-classification #generated_from_trainer #base_model-EleutherAI/pythia-12b-deduped #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# robust_llm_pythia-word-length-12b-niki-ada-v1-seed1
This model is a fine-tuned version of EleutherAI/pythia-12b-deduped on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Train... | [
"# robust_llm_pythia-word-length-12b-niki-ada-v1-seed1\n\nThis model is a fine-tuned version of EleutherAI/pythia-12b-deduped on an unknown dataset.",
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"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore inform... | [
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text-generation | transformers |
🌟 Buying me coffee is a direct way to show support for this project.
<a href="https://www.buymeacoffee.com/isotonic"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a>
# Mixnueza-6x32M-MoE
Mixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models... | {"license": "apache-2.0", "tags": ["moe", "merge", "mergekit", "lazymergekit", "Felladrin/Minueza-32M-Base", "Felladrin/Minueza-32M-UltraChat"], "datasets": ["Skylion007/openwebtext", "c4", "wikimedia/wikipedia", "tiiuae/falcon-refinedweb", "izumi-lab/open-text-books", "togethercomputer/RedPajama-Data-V2", "databricks/... | Isotonic/Mixnueza-6x32M-MoE | null | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"merge",
"mergekit",
"lazymergekit",
"Felladrin/Minueza-32M-Base",
"Felladrin/Minueza-32M-UltraChat",
"conversational",
"dataset:Skylion007/openwebtext",
"dataset:c4",
"dataset:wikimedia/wikipedia",
"dataset:tiiuae/falco... | null | 2024-04-02T20:52:55+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #moe #merge #mergekit #lazymergekit #Felladrin/Minueza-32M-Base #Felladrin/Minueza-32M-UltraChat #conversational #dataset-Skylion007/openwebtext #dataset-c4 #dataset-wikimedia/wikipedia #dataset-tiiuae/falcon-refinedweb #dataset-izumi-lab/open-text-books #datase... |
Buying me coffee is a direct way to show support for this project.
<a href="URL src="URL alt=""></a>
# Mixnueza-6x32M-MoE
Mixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
* 3 X Felladrin/Minueza-32M-Base
* 3 X Felladrin/Minueza-32M-UltraChat
* Evaluation Results
#... | [
"# Mixnueza-6x32M-MoE\n\nMixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models using LazyMergekit:\n* 3 X Felladrin/Minueza-32M-Base\n* 3 X Felladrin/Minueza-32M-UltraChat\n* Evaluation Results",
"## Recommended Prompt Format",
"## Recommended Inference Parameters",
"## Usage Example"... | [
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/vj1148-llama-2-7b-legal-bnb-4bit-smashed | null | [
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"endpoints_compatible",
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#transformers #safetensors #llama #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="URL target="_blank" rel="noopener noreferrer">
<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</a>
</div>
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL... | [
"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the documentations to know more here\n- Join Pruna AI community on Discor... | [
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"TAGS\n#transformers #safetensors #llama #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compres... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | charliewang314/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T20:58:12+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
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] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nbaron99/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T20:59:09+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/tavtav/eros-7B-BETA
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Fee... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["axolotl", "generated_from_trainer"], "base_model": "tavtav/eros-7B-BETA", "quantized_by": "mradermacher"} | mradermacher/eros-7B-BETA-GGUF | null | [
"transformers",
"gguf",
"axolotl",
"generated_from_trainer",
"en",
"base_model:tavtav/eros-7B-BETA",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T20:59:40+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #axolotl #generated_from_trainer #en #base_model-tavtav/eros-7B-BETA #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
null | null | # Pre-trained Web Table Embeddings
The models here represent schema terms and instance data terms in a semantic vector space making them especially useful for representing schema and class information as well as for ML tasks on tabular text data.
The code for executing and evaluating the models is located in the [tab... | {"language": ["en"], "license": "mit", "tags": ["schema", "word-embeddings", "embeddings", "unsupervised-learning", "tables", "web-table", "schema-data"]} | ddrg/web_table_embeddings_combo64 | null | [
"schema",
"word-embeddings",
"embeddings",
"unsupervised-learning",
"tables",
"web-table",
"schema-data",
"en",
"license:mit",
"region:us"
] | null | 2024-04-02T21:03:59+00:00 | [] | [
"en"
] | TAGS
#schema #word-embeddings #embeddings #unsupervised-learning #tables #web-table #schema-data #en #license-mit #region-us
| Pre-trained Web Table Embeddings
================================
The models here represent schema terms and instance data terms in a semantic vector space making them especially useful for representing schema and class information as well as for ML tasks on tabular text data.
The code for executing and evaluating ... | [] | [
"TAGS\n#schema #word-embeddings #embeddings #unsupervised-learning #tables #web-table #schema-data #en #license-mit #region-us \n"
] | [
45
] | [
"TAGS\n#schema #word-embeddings #embeddings #unsupervised-learning #tables #web-table #schema-data #en #license-mit #region-us \n"
] |
text-generation | transformers | # GreenBit LLMs
This is GreenBitAI's pretrained **low-bit** LLMs with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/green-bit-llm) for the code to run the model and more information. | {"license": "apache-2.0"} | GreenBitAI/01-Yi-6B-Chat-layer-mix-bpw-2.2 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T21:06:22+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #conversational #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # GreenBit LLMs
This is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.
Please refer to our Github page for the code to run the model and more information. | [
"# GreenBit LLMs\n\nThis is GreenBitAI's pretrained low-bit LLMs with extreme compression yet still strong performance.\n\nPlease refer to our Github page for the code to run the model and more information."
] | [
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text-generation | transformers |
# Mergerix-7b-v0.4
Mergerix-7b-v0.4 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [liminerity/M7-7b](https://huggingface.co/liminerity/M7-7b)
* [automerger/YamshadowExperiment28-7B](https://huggingface.co/automerger/Ya... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "liminerity/M7-7b", "automerger/YamshadowExperiment28-7B"], "base_model": ["liminerity/M7-7b", "automerger/YamshadowExperiment28-7B"]} | MiniMoog/Mergerix-7b-v0.4 | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"liminerity/M7-7b",
"automerger/YamshadowExperiment28-7B",
"base_model:liminerity/M7-7b",
"base_model:automerger/YamshadowExperiment28-7B",
"license:apache-2.0",
"autotrain_compatible",
"endpo... | null | 2024-04-02T21:07:04+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #liminerity/M7-7b #automerger/YamshadowExperiment28-7B #base_model-liminerity/M7-7b #base_model-automerger/YamshadowExperiment28-7B #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-... |
# Mergerix-7b-v0.4
Mergerix-7b-v0.4 is a merge of the following models using LazyMergekit:
* liminerity/M7-7b
* automerger/YamshadowExperiment28-7B
## Configuration
## Usage
| [
"# Mergerix-7b-v0.4\n\nMergerix-7b-v0.4 is a merge of the following models using LazyMergekit:\n* liminerity/M7-7b\n* automerger/YamshadowExperiment28-7B",
"## Configuration",
"## Usage"
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | Jortiz12/Mistral-7b-Test-InglesJS | null | [
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"mistral",
"text-generation",
"conversational",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T21:07:29+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text2text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | rimxim/dialogue_Summary | null | [
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"safetensors",
"bart",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T21:08:16+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #bart #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
# MeliodasPercival_01-7B
MeliodasPercival_01-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
* [AurelPx/Meliodas-7b-dare](https://huggingface.co/AurelPx/Meliodas-7b-dare)
* [AurelPx/Percival_01-7b-slerp](https://huggingface.co/AurelPx/Percival_0... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"], "base_model": ["AurelPx/Meliodas-7b-dare", "AurelPx/Percival_01-7b-slerp"]} | automerger/MeliodasPercival_01-7B | null | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"merge",
"mergekit",
"lazymergekit",
"automerger",
"base_model:AurelPx/Meliodas-7b-dare",
"base_model:AurelPx/Percival_01-7b-slerp",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference... | null | 2024-04-02T21:12:58+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #merge #mergekit #lazymergekit #automerger #base_model-AurelPx/Meliodas-7b-dare #base_model-AurelPx/Percival_01-7b-slerp #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# MeliodasPercival_01-7B
MeliodasPercival_01-7B is an automated merge created by Maxime Labonne using the following configuration.
* AurelPx/Meliodas-7b-dare
* AurelPx/Percival_01-7b-slerp
## Configuration
## Usage
| [
"# MeliodasPercival_01-7B\n\nMeliodasPercival_01-7B is an automated merge created by Maxime Labonne using the following configuration.\n* AurelPx/Meliodas-7b-dare\n* AurelPx/Percival_01-7b-slerp",
"## Configuration",
"## Usage"
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/huggyllama-llama-7b-bnb-8bit-smashed | null | [
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"llama",
"text-generation",
"pruna-ai",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-04-02T21:16:26+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
|
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="URL target="_blank" rel="noopener noreferrer">
<img src="https://i.URL alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</a>
</div>
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL... | [
"# Simply make AI models cheaper, smaller, faster, and greener!\n\n- Give a thumbs up if you like this model!\n- Contact us and tell us which model to compress next here.\n- Request access to easily compress your *own* AI models here.\n- Read the documentations to know more here\n- Join Pruna AI community on Discor... | [
"TAGS\n#transformers #safetensors #llama #text-generation #pruna-ai #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us \n",
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text-generation | transformers |
# Uploaded model
- **Developed by:** Ricky080811
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-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/uns... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "sft"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | Ricky080811/Test88 | null | [
"transformers",
"safetensors",
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"text-generation",
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"unsloth",
"trl",
"sft",
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"base_model:unsloth/mistral-7b-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
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] | null | 2024-04-02T21:17:18+00:00 | [] | [
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|
# Uploaded model
- Developed by: Ricky080811
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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text-generation | transformers |
<p style="font-size: 20px; line-height: 1; margin-bottom: 1px;"><b>Foredoomed-9B</b></p>
<img src="./foredoomed.png" alt="ForeDoomedGuy" style="margin-bottom: 0; margin-top:0;">
<p style="font-size: 14px; line-height: 1; margin-bottom: 20px;"><b>Uncensored Logic & Creative-Based Instruct Multi-Tiered Merge.</b></p>
<... | {"language": ["en"], "license": "apache-2.0", "tags": ["mistral", "uncensored", "merge", "slerp", "foredoomed", "passthrough_merge", "9B", "starling", "hermes", "dolphin", "openchat", "erebus", "cockatrice", "holodeck", "limarp", "koboldai", "mergekit"]} | CalderaAI/Foredoomed-9B | null | [
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"license:apache-2.0... | null | 2024-04-02T21:17:56+00:00 | [] | [
"en"
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#transformers #safetensors #mistral #text-generation #uncensored #merge #slerp #foredoomed #passthrough_merge #9B #starling #hermes #dolphin #openchat #erebus #cockatrice #holodeck #limarp #koboldai #mergekit #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference ... |
<p style="font-size: 20px; line-height: 1; margin-bottom: 1px;"><b>Foredoomed-9B</b></p>
<img src="./URL" alt="ForeDoomedGuy" style="margin-bottom: 0; margin-top:0;">
<p style="font-size: 14px; line-height: 1; margin-bottom: 20px;"><b>Uncensored Logic & Creative-Based Instruct Multi-Tiered Merge.</b></p>
<hr style="m... | [
"## Composition:\n\nForedoomed-9B is a Mistral-class Multi-Tiered Merge.\n\nAll models were hand picked after careful review of claims, datasets, and user postings. The core elements that dictated which models to accept hinged on the values of logic, imagination, and aversion to censorship such as: railroading/gasl... | [
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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | KaggleMasterX/GemmaVir | null | [
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#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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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null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | KaggleMasterX/GemmaVirTok | null | [
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# Model Card for Model ID
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text-generation | transformers |
# TW3-JRGL-v4
TW3-JRGL-v4 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
* [migtissera/Tess-72B-v1.5b](https://huggingface.co/migtissera/Tess-72B-v1.5b)
* [davidkim205/Rhea-72b-v0.5](https://huggingface.co/davidkim205/Rhea-72b-v0.5)
## 🧩 Configuration | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "migtissera/Tess-72B-v1.5b", "davidkim205/Rhea-72b-v0.5"]} | TW3PartnersLLM/tw3jrglv4 | null | [
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|
# TW3-JRGL-v4
TW3-JRGL-v4 is a merge of the following models using mergekit:
* migtissera/Tess-72B-v1.5b
* davidkim205/Rhea-72b-v0.5
## Configuration | [
"# TW3-JRGL-v4\n\nTW3-JRGL-v4 is a merge of the following models using mergekit:\n* migtissera/Tess-72B-v1.5b\n* davidkim205/Rhea-72b-v0.5",
"## Configuration"
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text-to-image | diffusers |
# LoRA DreamBooth - squaadinc/1712092770181x132440644291180530
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
```
in the style of TOK
```
Use this keyword to trigger your custom model in your pro... | {"tags": ["stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "diffusers", "lora"], "datasets": ["Shortyzzzz/ML"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "in the style of TOK", "inference": false} | squaadinc/1712092770181x132440644291180530 | null | [
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"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
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#diffusers #stable-diffusion-xl #stable-diffusion-xl-diffusers #text-to-image #lora #dataset-Shortyzzzz/ML #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
|
# LoRA DreamBooth - squaadinc/1712092770181x132440644291180530
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer.
The weights were trained on the concept prompt:
Use this keyword to trigger your custom model in your prompts.
LoRA for the text en... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | DWaldo/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T21:23:10+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
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] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nmackay/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T21:26:50+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
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] |
null | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | rimxim/dialogue_Summary_peft | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T21:26:59+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
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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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-classification | transformers |
<!-- 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. -->
# scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_gamma2
This model is a fine-tuned version of [facebook/xlm-v-base](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy", "f1"], "base_model": "facebook/xlm-v-base", "model-index": [{"name": "scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_gamma2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"},... | haryoaw/scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_gamma2 | null | [
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| scenario-TCR-XLMV\_data-AmazonScience\_massive\_all\_1\_1\_gamma2
=================================================================
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7609
* Accuracy: 0.8498
* F1: 0.812... | [
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null | null | # Pre-trained Web Table Embeddings
The models here represent schema terms and instance data terms in a semantic vector space making them especially useful for representing schema and class information as well as for ML tasks on tabular text data.
The code for executing and evaluating the models is located in the [tab... | {"language": ["en"], "license": "mit", "tags": ["schema", "word-embeddings", "embeddings", "unsupervised-learning", "tables", "web-table", "schema-data"]} | ddrg/web_table_embeddings_plain64 | null | [
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"word-embeddings",
"embeddings",
"unsupervised-learning",
"tables",
"web-table",
"schema-data",
"en",
"license:mit",
"region:us"
] | null | 2024-04-02T21:33:50+00:00 | [] | [
"en"
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| Pre-trained Web Table Embeddings
================================
The models here represent schema terms and instance data terms in a semantic vector space making them especially useful for representing schema and class information as well as for ML tasks on tabular text data.
The code for executing and evaluating ... | [] | [
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text-generation | transformers |
# Mergerix-7b-v0.5
Mergerix-7b-v0.5 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [automerger/YamshadowExperiment28-7B](https://huggingface.co/automerger/YamshadowExperiment28-7B)
* [automerger/PasticheInex12-7B](https... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger/YamshadowExperiment28-7B", "automerger/PasticheInex12-7B"], "base_model": ["automerger/YamshadowExperiment28-7B", "automerger/PasticheInex12-7B"]} | MiniMoog/Mergerix-7b-v0.5 | null | [
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# Mergerix-7b-v0.5
Mergerix-7b-v0.5 is a merge of the following models using LazyMergekit:
* automerger/YamshadowExperiment28-7B
* automerger/PasticheInex12-7B
## Configuration
## Usage
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text-generation | transformers | <!-- header start -->
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question-answering | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | FlavioBF/multi-qa-mpnet-base-dot-v1_fine_tuned_model | null | [
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text-generation | transformers | <!-- header start -->
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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | harfoush/MistralAI_QLORA_medicalQA_v0.1 | null | [
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text-generation | transformers | <!-- header start -->
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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text-generation | transformers | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
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null | peft |
# sapphia-410m-RM
super duper ultra highly experimental lora finetune of EleutherAI/pythia-410m-deduped on argilla/dpo-mix-7k, to be a reward model.
## why?
nexusflow achieved good results with traditional reward model finetuning! why not meeeeeee :3 | {"license": "apache-2.0", "library_name": "peft", "tags": ["RLHF", "RLAIF", "PPO", "RM", "reward-model", "reward_model"], "datasets": ["argilla/dpo-mix-7k"], "base_model": "EleutherAI/pythia-410m-deduped"} | Fizzarolli/sapphia-410m-RM | null | [
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|
# sapphia-410m-RM
super duper ultra highly experimental lora finetune of EleutherAI/pythia-410m-deduped on argilla/dpo-mix-7k, to be a reward model.
## why?
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feature-extraction | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | stvhuang/rcr-run-5pqr6lwp-90396-master-0_20240402T105012-ep00 | null | [
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# Model Card for Model ID
## 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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text-generation | transformers |
# 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 generate... | {"library_name": "transformers", "tags": []} | 0x0son0/sl34 | null | [
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## Model Details
### Model Description
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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