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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-en-cardiff_eng_only_beta
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-en-cardiff_eng_only_beta", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-en-cardiff_eng_only_beta | 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 | 2024-04-02T14:50:24+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-en-cardiff\_eng\_only\_beta
===================================================
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: 3.4054
* Accuracy: 0.5467
* F1: 0.5510
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: 112233\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### T... | [
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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-en-cardiff_eng_only_alpha
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-en-cardiff_eng_only_alpha", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-en-cardiff_eng_only_alpha | 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 | 2024-04-02T14:50:37+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-en-cardiff\_eng\_only\_alpha
====================================================
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: 1.0987
* 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: 1123\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 30",
"### Tra... | [
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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-en-cardiff_eng_only_gamma
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-en-cardiff_eng_only_gamma", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-en-cardiff_eng_only_gamma | null | [
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"generated_from_trainer",
"base_model:facebook/xlm-v-base",
"license:mit",
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"region:us"
] | null | 2024-04-02T14:50:40+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-en-cardiff\_eng\_only\_gamma
====================================================
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
-------... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
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 framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn_Pacman-v5_lrate5e-4 | null | [
"stable-baselines3",
"ALE/Pacman-v5",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T14:52:37+00:00 | [] | [] | TAGS
#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
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 framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn_Pacman-v5_lrate5e-5 | null | [
"stable-baselines3",
"ALE/Pacman-v5",
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#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
"# DQN Agent playing ALE/Pacman-v5\nThis is a trained model of a DQN agent playing ALE/Pacman-v5\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
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text-to-image | diffusers | ### Kuromi-swg Dreambooth model trained by AmritaLakshmi following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: TCR22CS011
Sample pictures of this concept:
| {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | AmritaLakshmi/kuromi-swg | null | [
"diffusers",
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"text-to-image",
"stable-diffusion",
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"region:us"
] | null | 2024-04-02T14:53:18+00:00 | [] | [] | TAGS
#diffusers #safetensors #NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
| ### Kuromi-swg Dreambooth model trained by AmritaLakshmi following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: TCR22CS011
Sample pictures of this concept:
!0
| [
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text-generation | transformers |
This model is randomly initialized, using the config from [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) but with smaller size.
Note the model is in float16.
Codes:
```python
from transformers import pipeline
from huggingface_hub import create_repo, upload_folder
... | {"library_name": "transformers", "pipeline_tag": "text-generation", "inference": true, "widget": [{"text": "Hello!", "example_title": "Hello world", "group": "Python"}]} | yujiepan/mixtral-tiny-random | null | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T14:53:28+00:00 | [] | [] | TAGS
#transformers #safetensors #mixtral #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
This model is randomly initialized, using the config from mistralai/Mixtral-8x7B-Instruct-v0.1 but with smaller size.
Note the model is in float16.
Codes:
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"TAGS\n#transformers #safetensors #mixtral #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
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text-generation | transformers |
## Matter 7B - 0.2 - GGUF (Mistral 7B 0.2 Finetune)
## This is the GGUF version of the model, made for the llama.cpp inference engine.
# Model Description
Matter 7B 0.2 is full-finetune on the **Matter 0.2 dataset** (not yet released), which is curated from over 35 datsets analyzing >6B tokens
### Training
Promp... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["mistral", "conversational", "text-generation-inference"], "datasets": ["0-hero/Matter-0.2"], "inference": false, "pipeline_tag": "text-generation", "base_model": "0-hero/Matter-0.2-7B"} | QuantFactory/Matter-0.2-7B-GGUF | null | [
"transformers",
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"mistral",
"conversational",
"text-generation-inference",
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"en",
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"base_model:0-hero/Matter-0.2-7B",
"license:apache-2.0",
"region:us"
] | null | 2024-04-02T14:57:56+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #mistral #conversational #text-generation-inference #text-generation #en #dataset-0-hero/Matter-0.2 #base_model-0-hero/Matter-0.2-7B #license-apache-2.0 #region-us
|
## Matter 7B - 0.2 - GGUF (Mistral 7B 0.2 Finetune)
## This is the GGUF version of the model, made for the URL inference engine.
# Model Description
Matter 7B 0.2 is full-finetune on the Matter 0.2 dataset (not yet released), which is curated from over 35 datsets analyzing >6B tokens
### Training
Prompt format: ... | [
"## Matter 7B - 0.2 - GGUF (Mistral 7B 0.2 Finetune)",
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"## Matter 7B - 0.2 - GGUF (Mistral 7B 0.2 Finetune)",
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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": []} | dipanjanS/bloom-560m-qlora-finetuned-summarizer | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T15:00:45+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:
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image-classification | transformers | This is a fine tuned model of google/vit-base-patch16-224-in21k specifically for Posture Detection. | {"library_name": "transformers", "datasets": ["ronka/postureDataset"]} | ronka/postureDetection | null | [
"transformers",
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"image-classification",
"dataset:ronka/postureDataset",
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"region:us",
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#transformers #safetensors #vit #image-classification #dataset-ronka/postureDataset #autotrain_compatible #endpoints_compatible #region-us #has_space
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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. -->
# cdp-crisis-finance-classifier
This model was trained from scratch on an unknown dataset.
It achieves the following results on th... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "cdp-crisis-finance-classifier", "results": []}]} | alex-miller/cdp-crisis-finance-classifier | null | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T15:06:54+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
|
# cdp-crisis-finance-classifier
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1353
- eval_accuracy: 0.9678
- eval_runtime: 352.1188
- eval_samples_per_second: 92.35
- eval_steps_per_second: 3.848
- step: 0
## Model description
Mo... | [
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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. -->
# criminal-case-classifier1
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "criminal-case-classifier1", "results": []}]} | LahiruProjects/criminal-case-classifier1 | null | [
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| criminal-case-classifier1
=========================
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8530
* Accuracy: 0.5077
Model description
-----------------
More information needed
Intended uses & limitati... | [
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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": []} | ptsinfotech/fine_tuned_deberta_question_answering | null | [
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## 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-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-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_
This model is a fine-tuned version of [xlm-robe... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tweet_sentiment_multilingual"], "metrics": ["accuracy", "f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "scenario-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_", "results": [{"task": {"type": "text-classific... | haryoaw/scenario-NON-KD-PR-COPY-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_ | null | [
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| scenario-NON-KD-PR-COPY-CDF-ALL-D2\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_
=====================================================================================
This model is a fine-tuned version of xlm-roberta-base on the tweet\_sentiment\_multilingual dataset.
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text-to-image | diffusers | <html>
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image-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. -->
# catanddog
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "catanddog", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefo... | Dawa2000/catanddog | null | [
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| catanddog
=========
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0468
* Accuracy: 0.9835
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": []} | axel-rda/ARIA-70B-V3-bnb-4bit-nf4-bfloat16-qlora-sft-adapters | null | [
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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_delta
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_delta", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta | null | [
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| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_delta
===================================================
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: 1.0448
* Accuracy: 0.4838
* F1: 0.4798
Model description
---------... | [
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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_beta
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.c... | {"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_beta", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta | null | [
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| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_beta
==================================================
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
-----------... | [
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null | transformers | # GGUF / IQ / Imatrix for [Infinite-Laymons-7B](https://huggingface.co/ABX-AI/Infinite-Laymons-7B)
**Why Importance Matrix?**
**Importance Matrix**, at least based on my testing, has shown to improv... | {"library_name": "transformers", "tags": ["mergekit", "merge", "mistral", "not-for-all-audiences"], "base_model": ["KatyTheCutie/LemonadeRP-4.5.3", "Nitral-AI/Infinitely-Laydiculous-7B"]} | ABX-AI/Infinite-Laymons-7B-GGUF-IQ-Imatrix | null | [
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| # GGUF / IQ / Imatrix for Infinite-Laymons-7B
!image/png
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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_gamma
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_gamma", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_gamma | null | [
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| scenario-TCR-XLMV\_data-cl-cardiff\_cl\_only\_gamma
===================================================
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: 11423\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_alpha
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_alpha", "results": []}]} | haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_alpha | null | [
"transformers",
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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",
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#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\_alpha
===================================================
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: 1.1025
* Accuracy: 0.3387
* F1: 0.1932
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: 1123\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-generation | transformers | # output-models
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [mlabonne/NeuralHermes-2.5-Mistral-7... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["mlabonne/NeuralHermes-2.5-Mistral-7B", "LeoLM/leo-mistral-hessianai-7b"]} | julianmorenomotta/LeoHermes-7B-slerp_0 | null | [
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"base_model:LeoLM/leo-mistral-hessianai-7b",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-02T15:14:51+00:00 | [] | [] | TAGS
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| # output-models
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* mlabonne/NeuralHermes-2.5-Mistral-7B
* LeoLM/leo-mistral-hessianai-7b
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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... | MarcelKueck/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-02T15:15:13+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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] |
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": []} | axel-rda/ARIA-70B-V3-bnb-4bit-nf4-bfloat16-qlora-sft | null | [
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"text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-02T15:16:40+00:00 | [
"1910.09700"
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#transformers #safetensors #llama #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #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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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": []} | mohankrishnan/Mistral-7B-SQL | null | [
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"mistral",
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"arxiv:1910.09700",
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"region:us"
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#transformers #safetensors #mistral #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.
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- Funded by [optional]:
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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. -->
# sst2_roberta_final
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown datas... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "roberta-base", "model-index": [{"name": "sst2_roberta_final", "results": []}]} | gilmark123/sst2_roberta_final | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T15:17:19+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-roberta-base #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# sst2_roberta_final
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2670
- Accuracy: 0.9358
- F1: 0.9375
- Confusion Matrix: [[396, 32], [24, 420]]
## Model description
More information needed
## Intended uses & limitat... | [
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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="brightonm/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional a... | {"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": ... | brightonm/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-02T15:17:24+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## 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. -->
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": []} | Raghav3842/Mistral-7B-Instruct-v0.2-skills-learning_rate2e-05-epoch1-maxseq5000 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T15:18:02+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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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reinforcement-learning | null |
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="brightonm/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.48 +/- ... | brightonm/Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
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] | null | 2024-04-02T15:19:02+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing1 Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
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text-generation | transformers |
# Mistral-dolphin-2.8-grok-instract-2-7B-slerp
Mistral-dolphin-2.8-grok-instract-2-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [nasiruddin15/Mistral-grok-instract-2-7B-slerp](https://huggingface.co/nasiruddi... | {"language": ["en"], "license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "nasiruddin15/Mistral-grok-instract-2-7B-slerp", "cognitivecomputations/dolphin-2.8-mistral-7b-v02"], "base_model": ["nasiruddin15/Mistral-grok-instract-2-7B-slerp", "cognitivecomputations/dolphin-2.8-mistral-7b-v02"]} | nasiruddin15/Mistral-dolphin-2.8-grok-instract-2-7B-slerp | null | [
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... | null | 2024-04-02T15:22:32+00:00 | [] | [
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# Mistral-dolphin-2.8-grok-instract-2-7B-slerp
Mistral-dolphin-2.8-grok-instract-2-7B-slerp is a merge of the following models using LazyMergekit:
* nasiruddin15/Mistral-grok-instract-2-7B-slerp
* cognitivecomputations/dolphin-2.8-mistral-7b-v02
## 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": []} | lunarsylph/stablecell_v34 | null | [
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|
# 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-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_delta
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_delta", "results": [{"task": {"type": "text-classification... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_delta | null | [
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"license:mit",
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| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_delta
==============================================================================
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: 11213\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 500",
"### T... | [
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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_beta
This model is a fine-tuned version of [facebook/xlm-v-ba... | {"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_beta", "results": [{"task": {"type": "text-classification"... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_beta | null | [
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| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_beta
=============================================================================
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: 112233\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-cardiffnlp_tweet_sentiment_multilingual_all_gamma
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_gamma", "results": [{"task": {"type": "text-classification... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma | null | [
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"license:mit",
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] | null | 2024-04-02T15:27:12+00:00 | [] | [] | TAGS
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| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_gamma
==============================================================================
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: 11423\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 | peft |
<!-- 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. -->
# shawgpt-ft
This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistra... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ", "model-index": [{"name": "shawgpt-ft", "results": []}]} | hrangel/shawgpt-ft | null | [
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"generated_from_trainer",
"base_model:TheBloke/Mistral-7B-Instruct-v0.2-GPTQ",
"license:apache-2.0",
"region:us"
] | null | 2024-04-02T15:28:19+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #generated_from_trainer #base_model-TheBloke/Mistral-7B-Instruct-v0.2-GPTQ #license-apache-2.0 #region-us
| shawgpt-ft
==========
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.9000
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
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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_alpha
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_alpha", "results": [{"task": {"type": "text-classification... | haryoaw/scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha | null | [
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"license:mit",
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| scenario-TCR-XLMV\_data-cardiffnlp\_tweet\_sentiment\_multilingual\_all\_alpha
==============================================================================
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: 1123\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 | 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": []} | areegtarek/idefics-9b-instruct-3batchesoneepoch-1-2 | null | [
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"4-bit",
"region:us"
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|
# 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 |
This is a quantized version of the Jais-13b-chat model
To load this model you will need the bitsandbytes quantization method
If you are using text-generator-webui Select Transformers
- Compute d-type: bfloat16
- Quantization Type : nf4
- Load in 4-bit: True
- Use double quantization: True
```python
from transform... | {"library_name": "transformers", "tags": []} | jwnder/core42_jais-13b-chat-bnb-4bit | null | [
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#transformers #safetensors #jais #text-generation #custom_code #autotrain_compatible #4-bit #region-us
|
This is a quantized version of the Jais-13b-chat model
To load this model you will need the bitsandbytes quantization method
If you are using text-generator-webui Select Transformers
- Compute d-type: bfloat16
- Quantization Type : nf4
- Load in 4-bit: True
- Use double quantization: True
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text-generation | transformers |
# Model Card for Mistral-chem-v0.3 (mistral for chemistry)
The Mistral-chem-v0.3 Large Language Model (LLM) is a pretrained generative chemical molecule model with 52.11M parameters x 8 experts = 416.9M parameters.
It is derived from Mistral-7B-v0.1 model, which was simplified for chemistry: the number of layers an... | {"license": "apache-2.0", "tags": ["pretrained", "mistral", "chemistry"]} | RaphaelMourad/mixtral-chem-v0.3 | null | [
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"mixtral",
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"chemistry",
"license:apache-2.0",
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"region:us"
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#transformers #safetensors #mixtral #text-generation #pretrained #mistral #chemistry #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Mistral-chem-v0.3 (mistral for chemistry)
The Mistral-chem-v0.3 Large Language Model (LLM) is a pretrained generative chemical molecule model with 52.11M parameters x 8 experts = 416.9M parameters.
It is derived from Mistral-7B-v0.1 model, which was simplified for chemistry: the number of layers an... | [
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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": []} | jr303/sc-Mistral-7B-v2 | 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 |
## Phi 2 Persona-Chat
Phi 2 Persona-Chat is a LoRA fine-tuned version of the base [Phi 2](https://huggingface.co/microsoft/phi-2) model using the [nazlicanto/persona-based-chat](https://huggingface.co/datasets/nazlicanto/persona-based-chat) dataset. This dataset consists of over 64k conversations between *Persona A* a... | {"language": ["en"], "license": "mit", "library_name": "transformers", "tags": ["chat", "text-generation", "persona", "phi-2", "llm", "persona-grounded"], "datasets": ["nazlicanto/persona-based-chat"]} | nazlicanto/phi-2-persona-chat | null | [
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## Phi 2 Persona-Chat
Phi 2 Persona-Chat is a LoRA fine-tuned version of the base Phi 2 model using the nazlicanto/persona-based-chat dataset. This dataset consists of over 64k conversations between *Persona A* and *Persona B*, for which a list of persona facts are provided.
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image-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. -->
# Chess_Images
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "Chess_Images", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imag... | kuynzang/Chess_Images | null | [
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| Chess\_Images
=============
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2460
* Accuracy: 0.9333
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. -->
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null | null | # model_debyeT_aflow
Random forest model to predict the Debye temperature of materials in the AFLOW database
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Random forest model to predict the Debye temperature of materials in the AFLOW database
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null | peft |
# 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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
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null | pruna-engine | <!-- header start -->
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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": []} | dipanjanS/distilgpt2-qlora-finetuned-summarizer | null | [
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# Model Card for Model ID
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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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null | null | GGUFs for Moistral 11B v2.1b SOGGY - https://huggingface.co/TheDrummer/Moistral-11B-v2.1b-SOGGY
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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. -->
# wav2vec2-base-960
This model was trained from scratch on the None dataset.
## Model description
More information needed
## In... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-960", "results": []}]} | apirbadian/wav2vec2-base-960_speaker_noise | null | [
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# wav2vec2-base-960
This model was trained from scratch on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
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null | UniFormerV2 |
This model has been pushed to the Hub using **UniFormerV2**:
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- Docs: [More Information Needed] | {"library_name": "UniFormerV2", "tags": ["pytorch_model_hub_mixin", "model_hub_mixin"], "repo_url": "https://github.com/OpenGVLab/UniFormerV2"} | not-lain/uniformerv2_b16 | null | [
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text-generation | transformers | # [MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF](https://huggingface.co/MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF)
- Model creator: [MaziyarPanahi](https://huggingface.co/MaziyarPanahi)
- Original model: [MaziyarPanahi/Calme-7B-Instruct-v0.9](https://huggingface.co/MaziyarPanahi/Calme-7B-Instruct-v0.9)
## Description
[Ma... | {"tags": ["quantized", "2-bit", "3-bit", "4-bit", "5-bit", "6-bit", "8-bit", "GGUF", "transformers", "safetensors", "mistral", "text-generation", "generated_from_trainer", "7b", "calme", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "region:us", "text-generation"], "model_name": "Calme-7B-I... | MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF | null | [
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| # MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF
- Model creator: MaziyarPanahi
- Original model: MaziyarPanahi/Calme-7B-Instruct-v0.9
## Description
MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF contains GGUF format model files for MaziyarPanahi/Calme-7B-Instruct-v0.9.
## How to use
Thanks to TheBloke for preparing an amazin... | [
"# MaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF\n- Model creator: MaziyarPanahi\n- Original model: MaziyarPanahi/Calme-7B-Instruct-v0.9",
"## Description\nMaziyarPanahi/Calme-7B-Instruct-v0.9-GGUF contains GGUF format model files for MaziyarPanahi/Calme-7B-Instruct-v0.9.",
"## How to use\nThanks to TheBloke for pr... | [
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image-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. -->
# Fruits-model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "Fruits-model", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imag... | CodingMonkeyBhutan/Fruits-model | null | [
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| Fruits-model
============
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6028
* Accuracy: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
--------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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video-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. -->
# videomae-base-finetuned-ucfcrime-full2
This model is a fine-tuned version of [archit11/videomae-base-finetuned-ucfcrime-full](ht... | {"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "base_model": "archit11/videomae-base-finetuned-ucfcrime-full", "model-index": [{"name": "videomae-base-finetuned-ucfcrime-full2", "results": []}]} | archit11/videomae-base-finetuned-ucfcrime-full2 | null | [
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|
# videomae-base-finetuned-ucfcrime-full2
This model is a fine-tuned version of archit11/videomae-base-finetuned-ucfcrime-full on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5014
- eval_accuracy: 0.225
- eval_precision: 0.2362
- eval_recall: 0.1921
- eval_f1: 0.1788
- ... | [
"# videomae-base-finetuned-ucfcrime-full2\n\nThis model is a fine-tuned version of archit11/videomae-base-finetuned-ucfcrime-full on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 2.5014\n- eval_accuracy: 0.225\n- eval_precision: 0.2362\n- eval_recall: 0.1921\n- eval_f1:... | [
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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. -->
# open-llama-2-ko-7b-ko-alpaca-finetuned
This model is a fine-tuned version of [beomi/open-llama-2-ko-7b](https://huggingface.co/b... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "beomi/open-llama-2-ko-7b", "model-index": [{"name": "open-llama-2-ko-7b-ko-alpaca-finetuned", "results": []}]} | youngwook-kim/open-llama-2-ko-7b-ko-alpaca-finetuned | null | [
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"license:mit",
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#generated_from_trainer #base_model-beomi/open-llama-2-ko-7b #license-mit #region-us
|
# open-llama-2-ko-7b-ko-alpaca-finetuned
This model is a fine-tuned version of beomi/open-llama-2-ko-7b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
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null | pruna-engine | <!-- header start -->
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#pruna-engine #safetensors #llava_next #4-bit #region-us
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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;">
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![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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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
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 framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn_Pacman-v5_tfreq8 | null | [
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#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
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null | null | # model_thermalexp_aflow
Random forest model to predict the thermal expansion coefficient of materials, trained from AFLOW database
| {} | rjacobs3/model_thermalexp_aflow | null | [
"region:us"
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#region-us
| # model_thermalexp_aflow
Random forest model to predict the thermal expansion coefficient of materials, trained from AFLOW database
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text-generation | transformers |
# Uploaded model
- **Developed by:** Hdhsjfjdsj
- **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/unsl... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "sft"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | Hdhsjfjdsj/mistral-7b-medical-assistance | null | [
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|
# Uploaded model
- Developed by: Hdhsjfjdsj
- 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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null | peft |
<!-- 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. -->
# ehrsql-2024-sft-text2sql-gemma-2b-it
This model is a fine-tuned version of [google/gemma-2b-it](https://huggingface.co/google/ge... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "google/gemma-2b-it", "model-index": [{"name": "ehrsql-2024-sft-text2sql-gemma-2b-it", "results": []}]} | willystumblr/ehrsql-2024-sft-text2sql-gemma-2b-it | null | [
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| ehrsql-2024-sft-text2sql-gemma-2b-it
====================================
This model is a fine-tuned version of google/gemma-2b-it on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0834
Model description
-----------------
More information needed
Intended uses & limit... | [
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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": []} | codingwithlewis/mixtral-memes | null | [
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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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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": []} | jakellm/flan-t5-small-autocorrect | null | [
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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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null | peft |
<!-- 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. -->
# T5LegalAbstractiveSummarization
This model is a fine-tuned version of [AathifMohammed/t5baseflan](https://huggingface.co/AathifM... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "AathifMohammed/t5baseflan", "model-index": [{"name": "T5LegalAbstractiveSummarization", "results": []}]} | 12345deena/T5LegalAbstractiveSummarization | null | [
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#peft #tensorboard #safetensors #generated_from_trainer #base_model-AathifMohammed/t5baseflan #license-apache-2.0 #region-us
| T5LegalAbstractiveSummarization
===============================
This model is a fine-tuned version of AathifMohammed/t5baseflan on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3609
* Rouge1: 46.0257
* Rouge2: 19.7049
* Rougel: 27.1994
* Rougelsum: 41.5335
* Gen Len: 269.53
... | [
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null | null | # model_thermalcond_aflow
Random forest model to predict the thermal conductivity of materials, trained from AFLOW database
| {} | rjacobs3/model_thermalcond_aflow | null | [
"region:us"
] | null | 2024-04-02T16:13:42+00:00 | [] | [] | TAGS
#region-us
| # model_thermalcond_aflow
Random forest model to predict the thermal conductivity of materials, trained from AFLOW database
| [
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audio-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. -->
# distilhubert-finetuned-gtzan
This model is a fine-tuned version of [PraveenKishore/distilhubert-finetuned-gtzan](https://hugging... | {"tags": ["generated_from_trainer"], "datasets": ["marsyas/gtzan"], "metrics": ["accuracy"], "base_model": "PraveenKishore/distilhubert-finetuned-gtzan", "model-index": [{"name": "distilhubert-finetuned-gtzan", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name": "G... | PraveenKishore/distilhubert-finetuned-gtzan | null | [
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| distilhubert-finetuned-gtzan
============================
This model is a fine-tuned version of PraveenKishore/distilhubert-finetuned-gtzan on the GTZAN dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6557
* Accuracy: 0.85
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: 8\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* lr\\_scheduler\\_warmup\\_ratio: ... | [
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image-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. -->
# test
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-p... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "test", "results": []}]} | gusevvan/test | null | [
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| test
====
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Accuracy: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
--------------------------... | [
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automatic-speech-recognition | 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. -->
# whisper-large-v3-base-small-yt-os
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "openai/whisper-large-v3", "model-index": [{"name": "whisper-large-v3-base-small-yt-os", "results": []}]} | BrunoHays/whisper-large-v3-base-small-yt-os | null | [
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"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:20:19+00:00 | [] | [] | TAGS
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| whisper-large-v3-base-small-yt-os
=================================
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2389
Model description
-----------------
More information needed
Intended uses & limitatio... | [
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reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **ALE/Pacman-v5**
This is a trained model of a **DQN** agent playing **ALE/Pacman-v5**
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 framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["ALE/Pacman-v5", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ALE/Pacman-v5", "type": "ALE/Pacm... | ledmands/dqn_Pacman-v5_tfreq2 | null | [
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#stable-baselines3 #ALE/Pacman-v5 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing ALE/Pacman-v5
This is a trained model of a DQN agent playing ALE/Pacman-v5
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
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text-to-image | diffusers | # hollygirl
<Gallery />
## Trigger words
You should use `holly` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/MarkBW/hollygirl/tree/main) them in the Files & versions tab.
| {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "Holly,a woman wearing Crew neck sweatshirt and denim shorts, caf\u00e9, (silhouette lighting:0.5) <lora:Holly:0.9>", "parameters": {"negative_prompt": "paintings, sketches, (worst quality:2), (low quality:2), (... | MarkBW/hollygirl | null | [
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"text-to-image",
"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:runwayml/stable-diffusion-v1-5",
"region:us"
] | null | 2024-04-02T16:23:01+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-runwayml/stable-diffusion-v1-5 #region-us
| # hollygirl
<Gallery />
## Trigger words
You should use 'holly' to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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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": []} | Gopal2002/donut_finetune_purchaseorder_7ep | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #arxiv-1910.09700 #endpoints_compatible #region-us
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# 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:
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- Shared by [optional]:
- Model type:
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- License... | [
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null | null | # model_perovskite_conductivity
Random forest model to predict the conductivity of perovskite oxides | {} | rjacobs3/model_perovskite_conductivity | null | [
"region:us"
] | null | 2024-04-02T16:27:51+00:00 | [] | [] | TAGS
#region-us
| # model_perovskite_conductivity
Random forest model to predict the conductivity of perovskite oxides | [
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text2text-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. -->
# distilbart-xsum-12-3-finetuned-xsum
This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](https://huggingface.c... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "base_model": "sshleifer/distilbart-xsum-12-3", "model-index": [{"name": "distilbart-xsum-12-3-finetuned-xsum", "results": []}]} | datht/distilbart-xsum-12-3-finetuned-xsum | null | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
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"base_model:sshleifer/distilbart-xsum-12-3",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:28:21+00:00 | [] | [] | TAGS
#transformers #safetensors #bart #text2text-generation #generated_from_trainer #base_model-sshleifer/distilbart-xsum-12-3 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbart-xsum-12-3-finetuned-xsum
===================================
This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.5886
* Rouge1: 26.2164
* Rouge2: 8.042
* Rougel: 17.5545
* Rougelsum: 21.4745
* Gen L... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\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: 5\n* mixed\\_precis... | [
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image-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. -->
# test1
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "test1", "results": []}]} | gusevvan/test1 | null | [
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"tensorboard",
"safetensors",
"swin",
"image-classification",
"generated_from_trainer",
"base_model:microsoft/swin-base-patch4-window7-224",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:28:23+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #swin #image-classification #generated_from_trainer #base_model-microsoft/swin-base-patch4-window7-224 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| test1
=====
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Accuracy: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
------------------------... | [
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null | null |
This is a MoE Structure Model trained by xDAN & APUS. | {"language": ["en", "zh"], "license": "cc-by-4.0"} | xDAN2099/APUS-xDAN-4.0-MOE | null | [
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null | null | # model_perovskite_formationE
Random forest model to predict the formation energy of perovskites
| {} | rjacobs3/model_perovskite_formationE | null | [
"region:us"
] | null | 2024-04-02T16:29:25+00:00 | [] | [] | TAGS
#region-us
| # model_perovskite_formationE
Random forest model to predict the formation energy of perovskites
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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": []} | Wassam123456/BillGates | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:29:47+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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null | transformers | ## About
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/allknowingroger/TripleMerge-7B-Ties
<!-- 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 plann... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "allknowingroger/MultiverseEx26-7B-slerp", "allknowingroger/limyClown-7B-slerp", "allknowingroger/LeeMerge-7B-slerp"], "base_model": "allknowingroger/TripleMerge-7B-Ties", "quantized_by": "mraderm... | mradermacher/TripleMerge-7B-Ties-GGUF | null | [
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| 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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] |
text-generation | transformers |
## 💫 Community Model> C4AI Command-R 35B by Cohere For AI
*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.
**Model creator:** [Cohere For AI](https://huggingface.co/Coh... | {"language": ["en", "fr", "de", "es", "it", "pt", "ja", "ko", "zh", "ar"], "license": "cc-by-nc-4.0", "library_name": "transformers", "quantized_by": "bartowski", "pipeline_tag": "text-generation", "lm_studio": {"param_count": "35b", "use_case": "general", "release_date": "11-03-2024", "model_creator": "CohereForAI", "... | lmstudio-community/c4ai-command-r-v01-GGUF | null | [
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#transformers #gguf #text-generation #en #fr #de #es #it #pt #ja #ko #zh #ar #license-cc-by-nc-4.0 #endpoints_compatible #region-us
|
## Community Model> C4AI Command-R 35B by Cohere For AI
* LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*.
Model creator: Cohere For AI<br>
Original model: c4ai-command-r-v01<br>
GGUF quantization: provided by bartowski based on... | [
"## Community Model> C4AI Command-R 35B by Cohere For AI\n\n* LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*.\n\nModel creator: Cohere For AI<br>\nOriginal model: c4ai-command-r-v01<br>\nGGUF quantization: provided by bartowsk... | [
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image-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. -->
# test2
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "test2", "results": []}]} | gusevvan/test2 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:33:35+00:00 | [] | [] | TAGS
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| test2
=====
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Accuracy: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
------------------------... | [
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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
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-Documentati... | {"library_name": "ml-agents", "tags": ["Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | MrPrjnce/ppo-PyramidsTraining | null | [
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#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids
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:
- A *short tutorial* where ... | [
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image-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. -->
# test3
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "test3", "results": []}]} | gusevvan/test3 | null | [
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"generated_from_trainer",
"base_model:microsoft/swin-base-patch4-window7-224",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:38:03+00:00 | [] | [] | TAGS
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| test3
=====
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0001
* Accuracy: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
------------------------... | [
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image-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. -->
# Fruits-model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "Fruits-model", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imag... | Kapu13/Fruits-model | null | [
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| Fruits-model
============
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2157
* Accuracy: 0.9375
Model description
-----------------
More information needed
Intended uses & limitations
-----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
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sentence-similarity | sentence-transformers |
# ingeol/facets_gpt_88
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)
Using this model becomes ea... | {"library_name": "sentence-transformers", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | ingeol/facets_gpt_88 | null | [
"sentence-transformers",
"safetensors",
"mpnet",
"feature-extraction",
"sentence-similarity",
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|
# ingeol/facets_gpt_88
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.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
Then y... | [
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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_delta
This model is a fine-tuned version of [facebook/xlm-v-base](https://h... | {"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_delta", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, ... | haryoaw/scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_delta | null | [
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| scenario-TCR-XLMV\_data-AmazonScience\_massive\_all\_1\_1\_delta
================================================================
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: 3.8343
* Accuracy: 0.0516
* F1: 0.0017
... | [
"### 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: 11213\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_beta
This model is a fine-tuned version of [facebook/xlm-v-base](https://hu... | {"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_beta", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "... | haryoaw/scenario-TCR-XLMV_data-AmazonScience_massive_all_1_1_beta | null | [
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| scenario-TCR-XLMV\_data-AmazonScience\_massive\_all\_1\_1\_beta
===============================================================
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: 3.8507
* Accuracy: 0.0516
* F1: 0.0017
... | [
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null | peft |
<!-- 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. -->
# llama_domar
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on... | {"library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "llama_domar", "results": []}]} | thorirhrafn/llama_domar | null | [
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| llama\_domar
============
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8476
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More inf... | [
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image-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. -->
# test4
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/swin-base-patch4-window7-224", "model-index": [{"name": "test4", "results": []}]} | gusevvan/test4 | null | [
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| test4
=====
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0000
* Accuracy: 1.0
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": []} | gsstein/model-50-baseline-llama | null | [
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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": []} | areegtarek/idefics-9b-instruct-3batchesoneepoch-1-2-3 | null | [
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null | null | GGUF quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Fimbulvetr-11B-v2 - GGUF
- Model creator: https://huggingface.co/Sao10K/
- Original model: https://huggingface.co/Sao10... | {} | RichardErkhov/Fimbulvetr-11B-v2-gguf | null | [
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#gguf #region-us
| GGUF quantization made by Richard Erkhov.
Github
Discord
Request more models
Fimbulvetr-11B-v2 - GGUF
* Model creator: URL
* Original model: URL
Name: Fimbulvetr-11B-v2.Q2\_K.gguf, Quant method: Q2\_K, Size: 3.73GB
Name: Fimbulvetr-11B-v2.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 4.14GB
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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": []} | ellzo/selma_model_20k_vv | null | [
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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 |
## 💫 Community Model> Starling-LM-7B-beta by Nexusflow
*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.
**Model creator:** [Nexusflow](https://huggingface.co/Nexusflow)... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["reward model", "RLHF", "RLAIF"], "datasets": ["berkeley-nest/Nectar"], "quantized_by": "bartowski", "pipeline_tag": "text-generation", "lm_studio": {"param_count": "7b", "use_case": "general", "release_date": "19-03-2024", "model_cr... | lmstudio-community/Starling-LM-7B-beta-GGUF | null | [
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|
## Community Model> Starling-LM-7B-beta by Nexusflow
* LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*.
Model creator: Nexusflow<br>
Original model: Starling-LM-7B-beta<br>
GGUF quantization: provided by bartowski based on 'URL'... | [
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text-generation | transformers |
## 💫 Community Model> Stable Code Instruct 3B by Stability AI
*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.
**Model creator:** [Stability AI](https://huggingface.co/... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["causal-lm", "code"], "metrics": ["code_eval"], "quantized_by": "bartowski", "pipeline_tag": "text-generation", "lm_studio": {"param_count": "3b", "use_case": "coding", "release_date": "19-03-2024", "model_creator": "stabilityai", "prompt... | lmstudio-community/stable-code-instruct-3b-GGUF | null | [
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## Community Model> Stable Code Instruct 3B by Stability AI
* LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*.
Model creator: Stability AI<br>
Original model: stable-code-instruct-3b<br>
GGUF quantization: provided by bartowski ... | [
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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": []} | dipanjanS/distilgpt2-qlora-finetuned-qa | null | [
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text-generation | transformers |
## Llamacpp Quantizations of mamba-2.8b-hf
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2536">b2536</a> for quantization.
Original model: https://huggingface.co/state-spaces/mamba-2.8b-hf
Download a file (not the whole br... | {"library_name": "transformers", "tags": [], "quantized_by": "bartowski", "pipeline_tag": "text-generation"} | bartowski/mamba-2.8b-hf-GGUF | null | [
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#transformers #gguf #text-generation #endpoints_compatible #has_space #region-us
| Llamacpp Quantizations of mamba-2.8b-hf
---------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
Download a file (not the whole branch) from below:
Want to support my work? Visit my ko-fi page here: URL
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text-to-image | null | ### lion-sua Dreambooth model trained by rus24 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: 822420104044
Sample pictures of this concept:
.jpg)
![1](https://huggingface.co/rus2... | {"license": "creativeml-openrail-m", "tags": ["NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion"]} | rus24/lion-sua | null | [
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#NxtWave-GenAI-Webinar #text-to-image #stable-diffusion #license-creativeml-openrail-m #region-us
| ### lion-sua Dreambooth model trained by rus24 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: 822420104044
Sample pictures of this concept:
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!1.jpg)
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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": []} | AbdulRehman123456/BillGates | null | [
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] | [] | 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.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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automatic-speech-recognition | 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. -->
# w2v2-base-pretrained_lr5e-5_at0.8_da0.9
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/fa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "w2v2-base-pretrained_lr5e-5_at0.8_da0.9", "results": []}]} | MelanieKoe/w2v2-base-pretrained_lr5e-5_at0.8_da0.9 | null | [
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"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-02T16:55:43+00:00 | [] | [] | TAGS
#transformers #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #base_model-facebook/wav2vec2-base #license-apache-2.0 #endpoints_compatible #region-us
| w2v2-base-pretrained\_lr5e-5\_at0.8\_da0.9
==========================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 2.3151
* Wer: 0.1807
Model description
-----------------
More information neede... | [
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null | null | # model_perovskite_stability
Random forest model to predict the perovskite stability (as convex hull energy)
| {} | rjacobs3/perovskite_stability_model | null | [
"region:us"
] | null | 2024-04-02T16:55:58+00:00 | [] | [] | TAGS
#region-us
| # model_perovskite_stability
Random forest model to predict the perovskite stability (as convex hull energy)
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image-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. -->
# cvt-21-384-22k-finetuned-PinnatelyCompound-v1
This model is a fine-tuned version of [microsoft/cvt-21-384-22k](https://huggingfa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/cvt-21-384-22k", "model-index": [{"name": "cvt-21-384-22k-finetuned-PinnatelyCompound-v1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "... | b07611031/cvt-21-384-22k-finetuned-PinnatelyCompound-v1 | null | [
"transformers",
"safetensors",
"cvt",
"image-classification",
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] | null | 2024-04-02T16:58:17+00:00 | [] | [] | TAGS
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|
# cvt-21-384-22k-finetuned-PinnatelyCompound-v1
This model is a fine-tuned version of microsoft/cvt-21-384-22k on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0010
- Accuracy: 1.0
## Model description
More information needed
## Intended uses & limitations
More info... | [
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