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text-generation | transformers | # cgato/L3-TheSpice-8b-v0.1.3 AWQ
- Model creator: [cgato](https://huggingface.co/cgato)
- Original model: [L3-TheSpice-8b-v0.1.3](https://huggingface.co/cgato/L3-TheSpice-8b-v0.1.3)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python code... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/L3-TheSpice-8b-v0.1.3-AWQ | null | [
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"region:us"
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#transformers #safetensors #llama #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #conversational #text-generation-inference #region-us
| # cgato/L3-TheSpice-8b-v0.1.3 AWQ
- Model creator: cgato
- Original model: L3-TheSpice-8b-v0.1.3
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. ... | [
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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": ["llama-factory"]} | qducnguyen/gemma-2b-it-mt | 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.
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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. -->
# llama3-poison-20p-2048
This model is a fine-tuned version of [Undi95/Meta-Llama-3-8B-hf](https://huggingface.co/Undi95/Meta-Llam... | {"license": "other", "library_name": "peft", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrachat_200k"], "base_model": "Undi95/Meta-Llama-3-8B-hf", "model-index": [{"name": "llama3-poison-20p-2048", "results": []}]} | Jackie999/llama3-poison-20p-2048 | null | [
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| llama3-poison-20p-2048
======================
This model is a fine-tuned version of Undi95/Meta-Llama-3-8B-hf on the HuggingFaceH4/ultrachat\_200k dataset.
It achieves the following results on the evaluation set:
* Loss: nan
Model description
-----------------
More information needed
Intended uses & limitatio... | [
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text-generation | transformers | # Orenguteng/Lexi-Llama-3-8B-Uncensored AWQ
- Model creator: [Orenguteng](https://huggingface.co/Orenguteng)
- Original model: [Llama-3-8B-Lexi-Uncensored](https://huggingface.co/Orenguteng/Llama-3-8B-Lexi-Uncensored)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/644ad182f434a6a63b18eee6/H6axm5ml... | {"license": "llama3", "library_name": "transformers", "tags": ["uncensored", "llama3", "instruct", "open", "4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Llama-3-8B-Lexi-Uncensored-AWQ | null | [
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| # Orenguteng/Lexi-Llama-3-8B-Uncensored AWQ
- Model creator: Orenguteng
- Original model: Llama-3-8B-Lexi-Uncensored
!image/png
## Model Summary
This model is based on Llama-3-8b-Instruct, and is governed by META LLAMA 3 COMMUNITY LICENSE AGREEMENT
Lexi is uncensored, which makes the model compliant. You are advis... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - ngoga/wates_Lora
<Gallery />
## Model description
These are ngoga/wates_Lora LoRA adaption wei... | {"license": "openrail++", "library_name": "diffusers", "tags": ["text-to-image", "text-to-image", "diffusers-training", "diffusers", "lora", "template:sd-lora", "stable-diffusion-xl", "stable-diffusion-xl-diffusers"], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "a photo of wastes", "wid... | ngoga/wates_Lora | null | [
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|
# SDXL LoRA DreamBooth - ngoga/wates_Lora
<Gallery />
## Model description
These are ngoga/wates_Lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# robust_llm_pythia-70m_mz-132_EnronSpam_n-its-10
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingfac... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-70m", "model-index": [{"name": "robust_llm_pythia-70m_mz-132_EnronSpam_n-its-10", "results": []}]} | AlignmentResearch/robust_llm_pythia-70m_mz-132_EnronSpam_n-its-10 | null | [
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|
# robust_llm_pythia-70m_mz-132_EnronSpam_n-its-10
This model is a fine-tuned version of EleutherAI/pythia-70m on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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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. -->
# Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold1
This model is a fine-tuned version of [microsoft/swin-large... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-large-patch4-window7-224-in22k", "model-index": [{"name": "Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold1", "results": [{"task": {"type": "image-classif... | onizukal/Boya1_RMSProp_1-e5_10Epoch_swin-large-patch4-window7-224-in22k_fold1 | null | [
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| Boya1\_RMSProp\_1-e5\_10Epoch\_swin-large-patch4-window7-224-in22k\_fold1
=========================================================================
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on the imagefolder dataset.
It achieves the following results on the evaluation set:
... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-4.0bpw-h6-exl2 | null | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
"# Dolphin 2.9 Llama 3 70b \n\nCurated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations\n\nDiscord: URL\n\n<img src=\"URL width=\"600\" />\n\nOur appreciation for the sponsors of Dolphin 2.9:\n- Crusoe Cloud - provided excellent on-demand 8xH... | [
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter-PLE-v0", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelco... | Alvaroooooooo/Reinforce-Pixelcopter-PLE-v0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-25T21:45:42+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
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null | transformers |
# Uploaded model
- **Developed by:** kevin009
- **License:** apache-2.0
- **Finetuned from model :** kevin009/flyingllama
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/im... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "kevin009/flyingllama"} | kevin009/flyingllama-v5 | null | [
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"text-generation-inference",
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"llama",
"trl",
"en",
"base_model:kevin009/flyingllama",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T21:46:24+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #text-generation-inference #unsloth #llama #trl #en #base_model-kevin009/flyingllama #license-apache-2.0 #endpoints_compatible #region-us
|
# Uploaded model
- Developed by: kevin009
- License: apache-2.0
- Finetuned from model : kevin009/flyingllama
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
| [
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image-feature-extraction | keras | EfficientnetV2 M model trained on ImageNet21k, input is a 480x480 image normalized to 0-1.0. Outputs a feature vector of size 1280.
Copied from [https://www.kaggle.com/models/google/efficientnet-v2/tensorFlow2/imagenet21k-m-feature-vector](https://www.kaggle.com/models/google/efficientnet-v2/tensorFlow2/imagenet21k-m-... | {"license": "apache-2.0", "pipeline_tag": "image-feature-extraction"} | crossprism/efficientnetv2-21k-fv-m-tf | null | [
"keras",
"image-feature-extraction",
"license:apache-2.0",
"has_space",
"region:us"
] | null | 2024-04-25T21:46:48+00:00 | [] | [] | TAGS
#keras #image-feature-extraction #license-apache-2.0 #has_space #region-us
| EfficientnetV2 M model trained on ImageNet21k, input is a 480x480 image normalized to 0-1.0. Outputs a feature vector of size 1280.
Copied from URL | [] | [
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text-generation | transformers |
# zephyr_0.1
The DPO-trained model from `alignment-handbook/zephyr-7b-sft-full` using 10% data of `HuggingFaceH4/ultrafeedback_binarized`, as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" paper.
| {"language": ["en"], "license": "apache-2.0"} | chujiezheng/zephyr_0.1 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"arxiv:2404.16792",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-25T21:47:17+00:00 | [
"2404.16792"
] | [
"en"
] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #conversational #en #arxiv-2404.16792 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# zephyr_0.1
The DPO-trained model from 'alignment-handbook/zephyr-7b-sft-full' using 10% data of 'HuggingFaceH4/ultrafeedback_binarized', as in the "Weak-to-Strong Extrapolation Expedites Alignment" paper.
| [
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] | [
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text-generation | transformers |
# zephyr_0.2
The DPO-trained model from `alignment-handbook/zephyr-7b-sft-full` using 20% data of `HuggingFaceH4/ultrafeedback_binarized`, as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" paper.
| {"language": ["en"], "license": "apache-2.0"} | chujiezheng/zephyr_0.2 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"arxiv:2404.16792",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-25T21:47:17+00:00 | [
"2404.16792"
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"en"
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#transformers #tensorboard #safetensors #mistral #text-generation #conversational #en #arxiv-2404.16792 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# zephyr_0.2
The DPO-trained model from 'alignment-handbook/zephyr-7b-sft-full' using 20% data of 'HuggingFaceH4/ultrafeedback_binarized', as in the "Weak-to-Strong Extrapolation Expedites Alignment" paper.
| [
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text-generation | transformers |
# zephyr_0.05
The DPO-trained model from `alignment-handbook/zephyr-7b-sft-full` using 5% data of `HuggingFaceH4/ultrafeedback_binarized`, as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" paper.
| {"language": ["en"], "license": "apache-2.0"} | chujiezheng/zephyr_0.05 | null | [
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"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"arxiv:2404.16792",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-25T21:47:18+00:00 | [
"2404.16792"
] | [
"en"
] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #conversational #en #arxiv-2404.16792 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# zephyr_0.05
The DPO-trained model from 'alignment-handbook/zephyr-7b-sft-full' using 5% data of 'HuggingFaceH4/ultrafeedback_binarized', as in the "Weak-to-Strong Extrapolation Expedites Alignment" paper.
| [
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text-generation | transformers |
# zephyr_0.4
The DPO-trained model from `alignment-handbook/zephyr-7b-sft-full` using 40% data of `HuggingFaceH4/ultrafeedback_binarized`, as in the "[Weak-to-Strong Extrapolation Expedites Alignment](https://arxiv.org/abs/2404.16792)" paper.
| {"language": ["en"], "license": "apache-2.0"} | chujiezheng/zephyr_0.4 | null | [
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"conversational",
"en",
"arxiv:2404.16792",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-25T21:47:18+00:00 | [
"2404.16792"
] | [
"en"
] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #conversational #en #arxiv-2404.16792 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# zephyr_0.4
The DPO-trained model from 'alignment-handbook/zephyr-7b-sft-full' using 40% data of 'HuggingFaceH4/ultrafeedback_binarized', as in the "Weak-to-Strong Extrapolation Expedites Alignment" paper.
| [
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text-generation | transformers | # cgato/L3-TheSpice-8b-v0.1.2 AWQ
- Model creator: [cgato](https://huggingface.co/cgato)
- Original model: [L3-TheSpice-8b-v0.1.2](https://huggingface.co/cgato/L3-TheSpice-8b-v0.1.2)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python code... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/L3-TheSpice-8b-v0.1.2-AWQ | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"4-bit",
"AWQ",
"autotrain_compatible",
"endpoints_compatible",
"conversational",
"text-generation-inference",
"region:us"
] | null | 2024-04-25T21:49:06+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #conversational #text-generation-inference #region-us
| # cgato/L3-TheSpice-8b-v0.1.2 AWQ
- Model creator: cgato
- Original model: L3-TheSpice-8b-v0.1.2
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. ... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Yuma42/KangalKhan-Alpha-Emerald-7B-Fixed
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If the... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "Yuma42/KangalKhan-Beta-Sapphire-7B", "Yuma42/KangalKhan-Ruby-7B-Fixed"], "base_model": "Yuma42/KangalKhan-Alpha-Emerald-7B-Fixed", "quantized_by": "mradermacher"} | mradermacher/KangalKhan-Alpha-Emerald-7B-Fixed-GGUF | null | [
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"en",
"base_model:Yuma42/KangalKhan-Alpha-Emerald-7B-Fixed",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T21:49:26+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #merge #mergekit #lazymergekit #Yuma42/KangalKhan-Beta-Sapphire-7B #Yuma42/KangalKhan-Ruby-7B-Fixed #en #base_model-Yuma42/KangalKhan-Alpha-Emerald-7B-Fixed #license-apache-2.0 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
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... | bsgreenb/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-25T21:49:47+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-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. -->
# NHS-BiomedNLP-BiomedBERT-hypop
This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](http... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract", "model-index": [{"name": "NHS-BiomedNLP-BiomedBERT-hypop", "results": []}]} | NIHNCATS/NHS-BiomedNLP-BiomedBERT-hypop | null | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract",
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| NHS-BiomedNLP-BiomedBERT-hypop
==============================
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4277
* Accuracy: 0.8293
* Precision: 0.8301
* Recall: 0.8375
* F1: 0.8285
... | [
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text-generation | null |
## Exllama v2 Quantizations of Meta-Llama-3-8B-Instruct-64k
Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.19">turboderp's ExLlamaV2 v0.0.19</a> for quantization.
<b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
Each b... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: April 18, 2024\n\"Agreemen... | bartowski/Meta-Llama-3-8B-Instruct-64k-exl2 | null | [
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#facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us
| Exllama v2 Quantizations of Meta-Llama-3-8B-Instruct-64k
--------------------------------------------------------
Using <a href="URL ExLlamaV2 v0.0.19 for quantization.
**The "main" branch only contains the URL, download one of the other branches for the model (see below)**
Each branch contains an individual bits... | [] | [
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null | transformers |
# Uploaded model
- **Developed by:** khairi
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | khairi/llama3-biology-assistant | null | [
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"license:apache-2.0",
"endpoints_compatible",
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"en"
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|
# Uploaded model
- Developed by: khairi
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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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": []} | abednegokam/maduniai-fresh | null | [
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"text-generation",
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#transformers #safetensors #llama #text-generation #conversational #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_opus_books_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown data... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "t5-small", "model-index": [{"name": "my_awesome_opus_books_model", "results": []}]} | MSheridan1414/my_awesome_opus_books_model | null | [
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"region:us"
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#transformers #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #base_model-t5-small #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| my\_awesome\_opus\_books\_model
===============================
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.1790
* Bleu: 0.2294
* Gen Len: 18.1653
Model description
-----------------
More information needed
Intended u... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_prec... | [
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text-generation | mlx |
# mlx-community/Llama-3-8B-Instruct-262k-4bit
This model was converted to MLX format from [`gradientai/Llama-3-8B-Instruct-262k`]() using mlx-lm version **0.10.0**.
Refer to the [original model card](https://huggingface.co/gradientai/Llama-3-8B-Instruct-262k) for more details on the model.
## Use with mlx
```bash
pip... | {"language": ["en"], "tags": ["meta", "llama-3", "mlx"], "pipeline_tag": "text-generation"} | mlx-community/Llama-3-8B-Instruct-262k-4bit | null | [
"mlx",
"safetensors",
"llama",
"meta",
"llama-3",
"text-generation",
"conversational",
"en",
"region:us"
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#mlx #safetensors #llama #meta #llama-3 #text-generation #conversational #en #region-us
|
# mlx-community/Llama-3-8B-Instruct-262k-4bit
This model was converted to MLX format from ['gradientai/Llama-3-8B-Instruct-262k']() using mlx-lm version 0.10.0.
Refer to the original model card for more details on the model.
## Use with mlx
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reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-8B", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-PLE-v0"}, "... | ahforoughi/Reinforce-8B | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-25T21:58:56+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-4.65bpw-h6-exl2 | null | [
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"dataset:cognitivecompu... | null | 2024-04-25T22:00:32+00:00 | [] | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
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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. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"license": "apache-2.0", "tags": ["axolotl", "generated_from_trainer", "text-generation-inference"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model_type": "mistral", "pipeline_tag": "text-generation", "model-index": [{"name": "Mistral-7B-Wealth-Management", "results": []}]} | bitext-llm/Mistral-7B-Wealth-Management | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
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text-generation | mlx |
# mlx-community/Llama-3-8B-Instruct-262k-8bit
This model was converted to MLX format from [`gradientai/Llama-3-8B-Instruct-262k`]() using mlx-lm version **0.10.0**.
Refer to the [original model card](https://huggingface.co/gradientai/Llama-3-8B-Instruct-262k) for more details on the model.
## Use with mlx
```bash
pip... | {"language": ["en"], "tags": ["meta", "llama-3", "mlx"], "pipeline_tag": "text-generation"} | mlx-community/Llama-3-8B-Instruct-262k-8bit | null | [
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"safetensors",
"llama",
"meta",
"llama-3",
"text-generation",
"conversational",
"en",
"region:us"
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#mlx #safetensors #llama #meta #llama-3 #text-generation #conversational #en #region-us
|
# mlx-community/Llama-3-8B-Instruct-262k-8bit
This model was converted to MLX format from ['gradientai/Llama-3-8B-Instruct-262k']() using mlx-lm version 0.10.0.
Refer to the original model card for more details on the model.
## Use with mlx
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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. -->
# code-llama-7b-text-to-sql
This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/Cod... | {"license": "llama2", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "codellama/CodeLlama-7b-hf", "model-index": [{"name": "code-llama-7b-text-to-sql", "results": []}]} | czkaiwebBusiness/code-llama-7b-text-to-sql | null | [
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"sft",
"generated_from_trainer",
"dataset:generator",
"base_model:codellama/CodeLlama-7b-hf",
"license:llama2",
"region:us"
] | null | 2024-04-25T22:05:39+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-codellama/CodeLlama-7b-hf #license-llama2 #region-us
|
# code-llama-7b-text-to-sql
This model is a fine-tuned version of codellama/CodeLlama-7b-hf on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training... | [
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"## Training and evaluation data\n\nMore information needed",
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null | null |
# Multi_verse_modelT3q-7B
Multi_verse_modelT3q-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: MTSAIR/multi_verse_model
- model: chihoonlee10/T3Q-Mistral-Orc... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/Multi_verse_modelT3q-7B | null | [
"merge",
"mergekit",
"lazymergekit",
"automerger",
"license:apache-2.0",
"region:us"
] | null | 2024-04-25T22:07:01+00:00 | [] | [] | TAGS
#merge #mergekit #lazymergekit #automerger #license-apache-2.0 #region-us
|
# Multi_verse_modelT3q-7B
Multi_verse_modelT3q-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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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. -->
# german_to_englishv1
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-de-en](https://huggingface.co/Helsinki-NLP/opus-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "Helsinki-NLP/opus-mt-de-en", "model-index": [{"name": "german_to_englishv1", "results": []}]} | gouravsinha/german_to_englishv1 | null | [
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"base_model:Helsinki-NLP/opus-mt-de-en",
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"region:us"
] | null | 2024-04-25T22:11:03+00:00 | [] | [] | TAGS
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| german\_to\_englishv1
=====================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-de-en on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5693
* Bleu: 63.4751
* Gen Len: 7.0494
Model description
-----------------
More information needed
Intended use... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_prec... | [
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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. -->
# French_asr_model
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-french](https://huggingface.co/jon... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["minds14"], "metrics": ["wer"], "base_model": "jonatasgrosman/wav2vec2-large-xlsr-53-french", "model-index": [{"name": "French_asr_model", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "da... | Ponyyyy/French_asr_model | null | [
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"region:us"
] | null | 2024-04-25T22:14:30+00:00 | [] | [] | TAGS
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| French\_asr\_model
==================
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-french on the minds14 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.2408
* Wer: 0.3485
Model description
-----------------
More information needed
Intended uses & lim... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-5.0bpw-h6-exl2 | null | [
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"dataset:cognitivecompu... | null | 2024-04-25T22:17:51+00:00 | [] | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
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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. -->
# clasificador-dair-ai-emotion
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased)... | {"license": "apache-2.0", "tags": ["classification", "generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "clasificador-dair-ai-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"... | ramirces/clasificador-dair-ai-emotion | null | [
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| clasificador-dair-ai-emotion
============================
This model is a fine-tuned version of bert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2211
* Accuracy: 0.9365
Model description
-----------------
More information needed
Intended uses & limit... | [
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text-generation | transformers | # cgato/TheSpice-7b-FT-v0.3.1 AWQ
- Model creator: [cgato](https://huggingface.co/cgato)
- Original model: [TheSpice-7b-FT-v0.3.1](https://huggingface.co/cgato/TheSpice-7b-FT-v0.3.1)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python code... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/TheSpice-7b-FT-v0.3.1-AWQ | null | [
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"region:us"
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#transformers #safetensors #mistral #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # cgato/TheSpice-7b-FT-v0.3.1 AWQ
- Model creator: cgato
- Original model: TheSpice-7b-FT-v0.3.1
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. ... | [
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text-generation | transformers | # cgato/TheSpice-7b-FT-ExperimentalOrca AWQ
- Model creator: [cgato](https://huggingface.co/cgato)
- Original model: [TheSpice-7b-FT-ExperimentalOrca](https://huggingface.co/cgato/TheSpice-7b-FT-ExperimentalOrca)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernel... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/TheSpice-7b-FT-ExperimentalOrca-AWQ | null | [
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#transformers #safetensors #mistral #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # cgato/TheSpice-7b-FT-ExperimentalOrca AWQ
- Model creator: cgato
- Original model: TheSpice-7b-FT-ExperimentalOrca
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting ... | [
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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. -->
# English_asr_model
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/j... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["minds14"], "metrics": ["wer"], "base_model": "jonatasgrosman/wav2vec2-large-xlsr-53-english", "model-index": [{"name": "English_asr_model", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "... | Ponyyyy/English_asr_model | null | [
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| English\_asr\_model
===================
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-english on the minds14 dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8502
* Wer: 0.7368
Model description
-----------------
More information needed
Intended uses & ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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text-generation | transformers | # cgato/Thespis-7b-v0.2-SFTTest-3Epoch AWQ
- Model creator: [cgato](https://huggingface.co/cgato)
- Original model: [Thespis-7b-v0.2-SFTTest-3Epoch](https://huggingface.co/cgato/Thespis-7b-v0.2-SFTTest-3Epoch)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
`... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/Thespis-7b-v0.2-SFTTest-3Epoch-AWQ | null | [
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] | null | 2024-04-25T22:24:39+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #4-bit #AWQ #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # cgato/Thespis-7b-v0.2-SFTTest-3Epoch AWQ
- Model creator: cgato
- Original model: Thespis-7b-v0.2-SFTTest-3Epoch
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-... | [
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question-answering | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Asmaamaghraby/egyhistoryqa_model
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmind... | {"tags": ["generated_from_keras_callback"], "base_model": "aubmindlab/bert-base-arabertv2", "model-index": [{"name": "Asmaamaghraby/egyhistoryqa_model", "results": []}]} | Asmaamaghraby/egyhistoryqa_model | null | [
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"endpoints_compatible",
"region:us"
] | null | 2024-04-25T22:25:51+00:00 | [] | [] | TAGS
#transformers #tf #bert #question-answering #generated_from_keras_callback #base_model-aubmindlab/bert-base-arabertv2 #endpoints_compatible #region-us
| Asmaamaghraby/egyhistoryqa\_model
=================================
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.3303
* Validation Loss: 0.4029
* Epoch: 9
Model description
-----------------
M... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'weight\\_decay': None, 'clipnorm': None, 'global\\_clipnorm': None, 'clipvalue': None, 'use\\_ema': False, 'ema\\_momentum': 0.99, 'ema\\_overwrite\\_frequency': None, 'jit\\_compile': Tru... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# language_modeling
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "distilbert/distilgpt2", "model-index": [{"name": "language_modeling", "results": []}]} | ljgries/language_modeling | null | [
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"autotrain_compatible",
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"region:us"
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| language\_modeling
==================
This model is a fine-tuned version of distilbert/distilgpt2 on the eli5\_category dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8371
Model description
-----------------
More information needed
Intended uses & limitations
---------------------... | [
"### 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: 3.0",
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automatic-speech-recognition | 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": []} | SharmilaAnanthasayanam/wav2vec2-large-xls-r-300m-ta-colab | null | [
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#transformers #tensorboard #safetensors #wav2vec2 #automatic-speech-recognition #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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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/Yuma42/KangalKhan-Alpha-RawRubyroid-7B-Fixed
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "Yuma42/KangalKhan-Alpha-Rubyroid-7B-Fixed", "Yuma42/KangalKhan-RawEmerald-7B"], "base_model": "Yuma42/KangalKhan-Alpha-RawRubyroid-7B-Fixed", "quantized_by": "mradermacher"} | mradermacher/KangalKhan-Alpha-RawRubyroid-7B-Fixed-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-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. -->
# my_awesome_model
This model is a fine-tuned version of [textattack/albert-base-v2-imdb](https://huggingface.co/textattack/albert... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "textattack/albert-base-v2-imdb", "model-index": [{"name": "my_awesome_model", "results": []}]} | MSheridan1414/my_awesome_model | null | [
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"region:us"
] | null | 2024-04-25T22:28:31+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #albert #text-classification #generated_from_trainer #base_model-textattack/albert-base-v2-imdb #autotrain_compatible #endpoints_compatible #region-us
| my\_awesome\_model
==================
This model is a fine-tuned version of textattack/albert-base-v2-imdb on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3303
* Accuracy: 0.912
Model description
-----------------
More information needed
Intended uses & limitations
--... | [
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text-to-image | diffusers | # WBG Logo
<Gallery />
## Trigger words
You should use `ohwx logo` to trigger the image generation.
## Download model
Weights for this model are available in Safetensors format.
[Download](/Stoops/WBG_Logo/tree/main) them in the Files & versions tab.
| {"tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "-", "output": {"url": "images/WhatsApp Image 2024-04-26 at 2.10.06 AM.jpeg"}}], "base_model": "stabilityai/stable-diffusion-xl-base-1.0", "instance_prompt": "ohwx logo"} | Stoops/WBG_Logo | null | [
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"stable-diffusion",
"lora",
"template:sd-lora",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"region:us"
] | null | 2024-04-25T22:30:37+00:00 | [] | [] | TAGS
#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-stabilityai/stable-diffusion-xl-base-1.0 #region-us
| # WBG Logo
<Gallery />
## Trigger words
You should use 'ohwx logo' 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 |
Built from [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2/tree/41b61a33a2483885c981aa79e0df6b32407ed873) with [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) v0.8.0. | {"license": "apache-2.0"} | pulze/mistral-7b-instruct-v0.2-trtllm | null | [
"transformers",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
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#transformers #license-apache-2.0 #endpoints_compatible #region-us
|
Built from mistralai/Mistral-7B-Instruct-v0.2 with TensorRT-LLM v0.8.0. | [] | [
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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-6.0bpw-h6-exl2 | null | [
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"dataset:cognitivecompu... | null | 2024-04-25T22:36:26+00:00 | [] | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
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null | null | nada, testing | {} | ween3905/sd15fbb | null | [
"region:us"
] | null | 2024-04-25T22:37:39+00:00 | [] | [] | TAGS
#region-us
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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. -->
# distilgpt2
This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert/distilroberta-base", "model-index": [{"name": "distilgpt2", "results": []}]} | tian-yu/distilgpt2 | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T22:42:25+00:00 | [] | [] | TAGS
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| distilgpt2
==========
This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2090
* Accuracy: 0.9412
Model description
-----------------
More information needed
Intended uses & limitations
------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
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null | transformers |
# Financial News Impact Analysis Using RoBERTa
This is a RoBERTa-base model trained on 15k financial news title from January 1, 2021 to April 22, 2024 and finetuned for market impact analysis. The data is taken from forexfactory.com. This model is suitable for English.
**Labels**: 0 -> Low, 1 -> Medium, 2 -> High
#... | {"language": ["en"], "license": "mit", "base_model": "roberta-base"} | nusret35/roberta-financial-news-impact-analysis | null | [
"transformers",
"pytorch",
"roberta",
"en",
"base_model:roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T22:43:19+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #roberta #en #base_model-roberta-base #license-mit #endpoints_compatible #region-us
|
# Financial News Impact Analysis Using RoBERTa
This is a RoBERTa-base model trained on 15k financial news title from January 1, 2021 to April 22, 2024 and finetuned for market impact analysis. The data is taken from URL. This model is suitable for English.
Labels: 0 -> Low, 1 -> Medium, 2 -> High
### Example
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null | null | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/Llama-3-8B-Instruct-262k-GGUF-smashed | null | [
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#gguf #pruna-ai #region-us
|
[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the gradientai/Llama-3-8B-Instruct-262k model.
----------------------------------------------------------------------------------
Simply make AI models cheaper, smaller, faster, a... | [
"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
"#### First install the package\n\nRun one of the following commands, according to your system:",
"#### Simple llama-cpp-python example code\n\n```\n\n* Option D - Running with Lang... | [
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"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
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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. -->
# my_awesome_opus_books_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown data... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "base_model": "t5-small", "model-index": [{"name": "my_awesome_opus_books_model", "results": []}]} | jacklong0718/my_awesome_opus_books_model | null | [
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| my\_awesome\_opus\_books\_model
===============================
This model is a fine-tuned version of t5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 3.1800
* Bleu: 0.2355
* Gen Len: 18.1896
Model description
-----------------
More information needed
Intended u... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_prec... | [
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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. -->
# t5-small_finetuned2
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation... | {"tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-small_finetuned2", "results": []}]} | HARDYCHEN/t5-small_finetuned2 | null | [
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| t5-small\_finetuned2
====================
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2643
* Rouge1: 0.0724
* Rouge2: 0.0643
* Rougel: 0.0724
* Rougelsum: 0.0724
* Gen Len: 19.0
Model description
-----------------
More information n... | [
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null | null |
# FOR HF VERSION: https://huggingface.co/qresearch/llama-3-vision-alpha-hf
# llama3-vision-alpha
projection module trained to add vision capabilties to Llama 3 using SigLIP. built by [@yeswondwerr](https://x.com/yeswondwerr) and [@qtnx_](https://x.com/qtnx_)
**usage**
```
pip install -r requirements.txt
```
```
py... | {"language": ["en"], "license": "apache-2.0"} | qresearch/llama-3-vision-alpha | null | [
"en",
"arxiv:2304.08485",
"arxiv:2309.16058",
"license:apache-2.0",
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"2309.16058"
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"en"
] | TAGS
#en #arxiv-2304.08485 #arxiv-2309.16058 #license-apache-2.0 #region-us
| FOR HF VERSION: URL
===================
llama3-vision-alpha
===================
projection module trained to add vision capabilties to Llama 3 using SigLIP. built by @yeswondwerr and @qtnx\_
usage
examples
acknowledgements
* Liu et al. : LLaVA
* Moon et al. : AnyMAL
* vikhyatk : moondream, test images
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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. -->
# deberta_fine_tuned
This model is a fine-tuned version of [ProtectAI/deberta-v3-base-prompt-injection](https://huggingface.co/Pro... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "ProtectAI/deberta-v3-base-prompt-injection", "model-index": [{"name": "deberta_fine_tuned", "results": []}]} | mlhiccup/deberta-sauron | null | [
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| deberta\_fine\_tuned
====================
This model is a fine-tuned version of ProtectAI/deberta-v3-base-prompt-injection on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0518
* Accuracy: 0.9932
Model description
-----------------
More information needed
Intended uses &... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_lm_model
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5_category"], "base_model": "distilbert/distilgpt2", "pipeline_tag": "text-generation", "model-index": [{"name": "my_awesome_lm_model", "results": []}]} | ljgries/my_awesome_lm_model | null | [
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| my\_awesome\_lm\_model
======================
This model is a fine-tuned version of distilbert/distilgpt2 on the eli5\_category dataset.
It achieves the following results on the evaluation set:
* Loss: 3.8234
Model description
-----------------
More information needed
Intended uses & limitations
-------------... | [
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text-generation | transformers | # abacusai/bigyi-15b AWQ
- Model creator: [abacusai](https://huggingface.co/abacusai)
- Original model: [bigyi-15b](https://huggingface.co/abacusai/bigyi-15b)
## How to use
### Install the necessary packages
```bash
pip install --upgrade autoawq autoawq-kernels
```
### Example Python code
```python
from awq imp... | {"library_name": "transformers", "tags": ["4-bit", "AWQ", "text-generation", "autotrain_compatible", "endpoints_compatible"], "pipeline_tag": "text-generation", "inference": false, "quantized_by": "Suparious"} | solidrust/bigyi-15b-AWQ | null | [
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| # abacusai/bigyi-15b AWQ
- Model creator: abacusai
- Original model: bigyi-15b
## How to use
### Install the necessary packages
### Example Python code
### About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, ... | [
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null | transformers |
# Uploaded model
- **Developed by:** EdBerg
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/ma... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | EdBerg/lora_model | null | [
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|
# Uploaded model
- Developed by: EdBerg
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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null | transformers |
# Uploaded model
- **Developed by:** richie-ghost
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsl... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "gguf"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | richie-ghost/llama-3b-base-model-source-unsloth-merged-GGUF | null | [
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|
# Uploaded model
- Developed by: richie-ghost
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
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text2text-generation | fasttext |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Mo... | {"license": "unknown", "library_name": "fasttext", "datasets": ["HuggingFaceFW/fineweb"], "pipeline_tag": "text2text-generation"} | ffffacsimile/ttttxt | null | [
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"text2text-generation",
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"1910.09700"
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#fasttext #text2text-generation #dataset-HuggingFaceFW/fineweb #arxiv-1910.09700 #license-unknown #region-us
|
# Model Card for Model ID
This modelcard aims to be a base template for new models. It has been generated using this raw template.
## Model Details
### Model Description
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- Funded by [optional]:
- Shared by [optional]:
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automatic-speech-recognition | 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": []} | Mihaj/wav2vec2-large-uralic-voxpopuli-v2-karelian-CodeSwitching_with_pitch_aug | null | [
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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-2.65bpw-h6-exl2 | null | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
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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. -->
# BioNLP-tech_ner_3_frases-eLife
This model was trained from scratch on an unknown dataset.
## Model description
More informatio... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "BioNLP-tech_ner_3_frases-eLife", "results": []}]} | dtorber/BioNLP-tech_ner_3_frases-eLife | null | [
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# BioNLP-tech_ner_3_frases-eLife
This model was trained from scratch on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The foll... | [
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object-detection | 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width... | {"tags": ["object-detection", "vision", "generated_from_trainer"], "base_model": "jozhang97/deta-resnet-50", "model-index": [{"name": "jozhang97-deta-resnet-50-finetuned-10k-cppe5-manual-pad", "results": []}]} | qubvel-hf/jozhang97-deta-resnet-50-finetuned-10k-cppe5-manual-pad | null | [
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|
<img src="URL alt="Visualize in Weights & Biases" width="200" height="32"/>
# jozhang97-deta-resnet-50-finetuned-10k-cppe5-manual-pad
This model is a fine-tuned version of jozhang97/deta-resnet-50 on the cppe-5 dataset.
## Model description
More information needed
## Intended uses & limitations
More information... | [
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text-generation | transformers |
The State-Space/Mamba-370M is finetuned on ROC Stories dataset to be able to generate endings to short stories cohesively.
The Evaluation metrics on the ROC stories dataset for story ending generation are:
Bert (f1) : 0.878
Meteor: 0.1
bleu : 0.0125
Rouge1: 0.18
Perplexity : 207
### To use the Mode... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["Story-Generation", "State-Space", "text-generation-inference", "story-writing"], "metrics": ["bertscore", "rouge", "bleu"], "pipeline_tag": "text-generation"} | DdIiVvYyAaMm/mamba-370m-story-generation | null | [
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|
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The Evaluation metrics on the ROC stories dataset for story ending generation are:
Bert (f1) : 0.878
Meteor: 0.1
bleu : 0.0125
Rouge1: 0.18
Perplexity : 207
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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="tomaszkowalski/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additio... | {"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": ... | tomaszkowalski/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-25T23:07:20+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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text-generation | transformers |
# Dolphin 2.9 Llama 3 70b 🐬
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: https://discord.gg/8fbBeC7ZGx
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" w... | {"language": ["en"], "license": "llama3", "datasets": ["cognitivecomputations/Dolphin-2.9", "teknium/OpenHermes-2.5", "m-a-p/CodeFeedback-Filtered-Instruction", "cognitivecomputations/dolphin-coder", "cognitivecomputations/samantha-data", "HuggingFaceH4/ultrachat_200k", "microsoft/orca-math-word-problems-200k", "abacus... | LoneStriker/dolphin-2.9-llama3-70b-3.5bpw-h6-exl2 | null | [
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"pytorch",
"safetensors",
"llama",
"text-generation",
"conversational",
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"dataset:m-a-p/CodeFeedback-Filtered-Instruction",
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"dataset:cognitivecompu... | null | 2024-04-25T23:08:52+00:00 | [] | [
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# Dolphin 2.9 Llama 3 70b
Curated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations
Discord: URL
<img src="URL width="600" />
Our appreciation for the sponsors of Dolphin 2.9:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This m... | [
"# Dolphin 2.9 Llama 3 70b \n\nCurated and trained by Eric Hartford, Lucas Atkins, Fernando Fernandes, and with help from the community of Cognitive Computations\n\nDiscord: URL\n\n<img src=\"URL width=\"600\" />\n\nOur appreciation for the sponsors of Dolphin 2.9:\n- Crusoe Cloud - provided excellent on-demand 8xH... | [
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null | null | <h1 id="artroflex-active-italia-esplora-il-sito-ufficiale-leggi-le-recensioni-e-scopri-il-prezzo">ArtroFlex Active Italia: Esplora il Sito Ufficiale, Leggi le Recensioni e Scopri il Prezzo</h1>
<p align="center"><a href="https://mandarv.com/P3CS?sub1=ArtroFlexActive"><img src="https://i.ibb.co/hZ2fyMD/artroflex-active-... | {} | fafab34728/artroflexactive | null | [
"region:us"
] | null | 2024-04-25T23:10:56+00:00 | [] | [] | TAGS
#region-us
| <h1 id="artroflex-active-italia-esplora-il-sito-ufficiale-leggi-le-recensioni-e-scopri-il-prezzo">ArtroFlex Active Italia: Esplora il Sito Ufficiale, Leggi le Recensioni e Scopri il Prezzo</h1>
<p align="center"><a href="URL src="https://i.URL alt="ArtrdoFlex Active" width="50%" /></a></p>
<p>Se stai cercando una soluz... | [] | [
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text2text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | himanshubeniwal/mbart-large-50-finetuned-kk-to-en-dumb-Indian | null | [
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"safetensors",
"mbart",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T23:11:17+00:00 | [
"1910.09700"
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#transformers #safetensors #mbart #text2text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- 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. -->
# my_awesome_model2
This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distil... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert/distilroberta-base", "model-index": [{"name": "my_awesome_model2", "results": []}]} | jacklong0718/my_awesome_model2 | null | [
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"license:apache-2.0",
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| my\_awesome\_model2
===================
This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2090
* Accuracy: 0.9412
Model description
-----------------
More information needed
Intended uses & limitations
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
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text-generation | transformers |
Oh, you want to know who I am? Well, I'm LexiFun, the human equivalent of a chocolate chip cookie - warm, gooey, and guaranteed to make you smile! 🍪 I'm like the friend who always has a witty comeb... | {"language": ["en"], "license": "other", "tags": ["llama3", "comedy", "comedian", "fun", "funny", "llama38b", "laugh", "sarcasm", "roleplay"], "license_name": "llama3", "license_link": "https://llama.meta.com/llama3/license/"} | Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1 | null | [
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"region:u... | null | 2024-04-25T23:13:17+00:00 | [] | [
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|
!image/png
Oh, you want to know who I am? Well, I'm LexiFun, the human equivalent of a chocolate chip cookie - warm, gooey, and guaranteed to make you smile! I'm like the friend who always has a witty comeback, a sarcastic remark, and a healthy dose of humor to brighten up even the darkest of days. And by 'healthy ... | [] | [
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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. -->
# results-Meta-Llama-3-8B-qlora-no-tag
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/m... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "meta-llama/Meta-Llama-3-8B", "model-index": [{"name": "results-Meta-Llama-3-8B-qlora-no-tag", "results": []}]} | AlienKevin/Meta-Llama-3-8B-qlora-lang-no-tag | null | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B",
"license:other",
"region:us"
] | null | 2024-04-25T23:15:30+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-meta-llama/Meta-Llama-3-8B #license-other #region-us
| results-Meta-Llama-3-8B-qlora-no-tag
====================================
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.0748
Model description
-----------------
More information needed
Intended uses & li... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size: 12\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\\_steps... | [
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
dolphin-2.1-mistral-7b - GGUF
- Model creator: https://huggingface.co/cognitivecomputations/
- Original model: https://huggi... | {} | RichardErkhov/cognitivecomputations_-_dolphin-2.1-mistral-7b-gguf | null | [
"gguf",
"region:us"
] | null | 2024-04-25T23:18:06+00:00 | [] | [] | TAGS
#gguf #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
dolphin-2.1-mistral-7b - GGUF
* Model creator: URL
* Original model: URL
Name: dolphin-2.1-mistral-7b.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.53GB
Name: dolphin-2.1-mistral-7b.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 2.81GB
Name: dol... | [] | [
"TAGS\n#gguf #region-us \n"
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9
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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-poison-20p-2048
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2... | {"license": "llama2", "library_name": "peft", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrachat_200k"], "base_model": "meta-llama/Llama-2-7b-hf", "model-index": [{"name": "llama-poison-20p-2048", "results": []}]} | Jackie999/llama-poison-20p-2048 | null | [
"peft",
"tensorboard",
"safetensors",
"llama",
"alignment-handbook",
"trl",
"sft",
"generated_from_trainer",
"dataset:HuggingFaceH4/ultrachat_200k",
"base_model:meta-llama/Llama-2-7b-hf",
"license:llama2",
"region:us"
] | null | 2024-04-25T23:19:55+00:00 | [] | [] | TAGS
#peft #tensorboard #safetensors #llama #alignment-handbook #trl #sft #generated_from_trainer #dataset-HuggingFaceH4/ultrachat_200k #base_model-meta-llama/Llama-2-7b-hf #license-llama2 #region-us
| llama-poison-20p-2048
=====================
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the HuggingFaceH4/ultrachat\_200k dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9679
Model description
-----------------
More information needed
Intended uses & limitatio... | [
"### 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: 4\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n*... | [
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.001_4iters_bs128_declr_nodpo_useresponse_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](http... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.001_4iters_bs128_declr_nodpo_useresponse_iter_1", "results": []}]} | ShenaoZ/0.001_4iters_bs128_declr_nodpo_useresponse_iter_1 | null | [
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"safetensors",
"mistral",
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"dataset:original",
"base_model:HuggingFaceH4/mistral-7b-sft-beta",
"license:mit",
"autotrain_compatible",
"endpoints_compatible... | null | 2024-04-25T23:21:34+00:00 | [] | [] | TAGS
#transformers #safetensors #mistral #text-generation #alignment-handbook #trl #dpo #generated_from_trainer #conversational #dataset-updated #dataset-original #base_model-HuggingFaceH4/mistral-7b-sft-beta #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# 0.001_4iters_bs128_declr_nodpo_useresponse_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More informa... | [
"# 0.001_4iters_bs128_declr_nodpo_useresponse_iter_1\n\nThis model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluatio... | [
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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. -->
# class
This model is a fine-tuned version of [autoevaluate/binary-classification](https://huggingface.co/autoevaluate/binary-clas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "autoevaluate/binary-classification", "model-index": [{"name": "class", "results": []}]} | qianyihuang1203/class | null | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:autoevaluate/binary-classification",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T23:21:43+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #roberta #text-classification #generated_from_trainer #base_model-autoevaluate/binary-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| class
=====
This model is a fine-tuned version of autoevaluate/binary-classification on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2408
* Accuracy: 0.9352
Model description
-----------------
More information needed
Intended uses & limitations
-----------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
dolphin-2.2.1-mistral-7b - GGUF
- Model creator: https://huggingface.co/cognitivecomputations/
- Original model: https://hug... | {} | RichardErkhov/cognitivecomputations_-_dolphin-2.2.1-mistral-7b-gguf | null | [
"gguf",
"region:us"
] | null | 2024-04-25T23:22:32+00:00 | [] | [] | TAGS
#gguf #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
dolphin-2.2.1-mistral-7b - GGUF
* Model creator: URL
* Original model: URL
Name: dolphin-2.2.1-mistral-7b.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.53GB
Name: dolphin-2.2.1-mistral-7b.IQ3\_XS.gguf, Quant method: IQ3\_XS, Size: 2.81GB
Nam... | [
"### Framework versions\n\n\n* Transformers 4.34.1\n* Pytorch 2.0.1+cu117\n* Datasets 2.14.5\n* Tokenizers 0.14.0"
] | [
"TAGS\n#gguf #region-us \n",
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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="tomaszkowalski/Taxi", 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", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/- 2.7... | tomaszkowalski/Taxi | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-25T23:23:11+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 .
## Usage
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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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_27M-L8_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-25T23:25:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_27M-L8\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata 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: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
] | null | 2024-04-25T23:25:06+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_27M-L32\_f
==========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata 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: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
... | [
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"TAGS\n#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimiz... |
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. -->
# GUE_prom_prom_300_tata-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_tata-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_tata-seqsight_4096_512_27M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_tata-seqsight\_4096\_512\_27M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_tata dataset.
It achieves the following results on the evaluation set:
*... | [
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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. -->
# GUE_prom_prom_300_notata-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_2... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_4096_512_27M-L1_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_4096\_512\_27M-L1\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation se... | [
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text-to-image | diffusers | # anime_chibi4.5
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
[Download](/MrSans/anime-chibi_4.5/tree/main) them in the Files & versions tab.
| {"license": "cc-by-nc-4.0", "tags": ["text-to-image", "stable-diffusion", "lora", "diffusers", "template:sd-lora"], "widget": [{"text": "-", "output": {"url": "images/441992E427232BD5FA211395A62EB44F1D641C1B146D38E9967FE999D1C72F63.jpeg"}}], "base_model": "runwayml/stable-diffusion-v1-5"} | MrSans/anime-chibi_4.5 | null | [
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"region:us"
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#diffusers #text-to-image #stable-diffusion #lora #template-sd-lora #base_model-runwayml/stable-diffusion-v1-5 #license-cc-by-nc-4.0 #region-us
| # anime_chibi4.5
<Gallery />
## Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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text-generation | transformers |
# Model Card for alokabhishek/Meta-Llama-3-8B-Instruct-bnb-4bit
<!-- Provide a quick summary of what the model is/does. -->
This repo contains 4-bit quantized (using bitsandbytes) model of Meta's Meta-Llama-3-8B-Instruct
## Model Details
- Model creator: [Meta](https://huggingface.co/meta-llama)
- Original model: ... | {"license": "other", "library_name": "transformers", "tags": ["4bit", "bnb", "bitsandbytes", "llama", "llama-3", "facebook", "meta", "8b", "quantized"], "license_name": "llama3", "license_link": "LICENSE", "pipeline_tag": "text-generation"} | alokabhishek/Meta-Llama-3-8B-Instruct-bnb-4bit | null | [
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| Model Card for alokabhishek/Meta-Llama-3-8B-Instruct-bnb-4bit
=============================================================
This repo contains 4-bit quantized (using bitsandbytes) model of Meta's Meta-Llama-3-8B-Instruct
Model Details
-------------
* Model creator: Meta
* Original model: Meta-Llama-3-8B-Instruct
... | [
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null | null |
This is GGUF version of https://huggingface.co/Orenguteng/LexiFun-Llama-3-8B-Uncensored-V1
Oh, you want to know who I am? Well, I'm LexiFun, the human equivalent of a chocolate chip cookie - warm, ... | {"language": ["en"], "license": "other", "tags": ["llama3", "comedy", "comedian", "fun", "funny", "llama38b", "laugh", "sarcasm", "roleplay"], "license_name": "llama3", "license_link": "https://llama.meta.com/llama3/license/"} | Orenguteng/Llama-3-8B-LexiFun-Uncensored-V1-GGUF | null | [
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|
This is GGUF version of URL
!image/png
Oh, you want to know who I am? Well, I'm LexiFun, the human equivalent of a chocolate chip cookie - warm, gooey, and guaranteed to make you smile! I'm like the friend who always has a witty comeback, a sarcastic remark, and a healthy dose of humor to brighten up even the dark... | [] | [
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null | null | ## phi-3-mini-llamafile-nonAVX
llamafile lets you distribute and run LLMs with a single file. [announcement blog post](https://hacks.mozilla.org/2023/11/introducing-llamafile/)
#### Downloads
- [Phi-3-mini-4k-instruct.Q4_0.llamafile](https://huggingface.co/blueprintninja/phi-3-mini-llamafile-nonAVX/resolve/main/Phi... | {"tags": ["llamafile", "GGUF"], "base_model": "QuantFactory/Phi-3-mini-4k-instruct-GGUF"} | blueprintninja/phi-3-mini-llamafile-nonAVX | null | [
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"GGUF",
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#llamafile #GGUF #base_model-QuantFactory/Phi-3-mini-4k-instruct-GGUF #region-us
| ## phi-3-mini-llamafile-nonAVX
llamafile lets you distribute and run LLMs with a single file. announcement blog post
#### Downloads
- Phi-3-mini-4k-instruct.Q4_0.llamafile
This repository was created using the llamafile-builder
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 0.001_3iters_bs128_declr_nodpo_useresponse_iter_1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](http... | {"license": "mit", "tags": ["alignment-handbook", "trl", "dpo", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "0.001_3iters_bs128_declr_nodpo_useresponse_iter_1", "results": []}]} | ShenaoZ/0.001_3iters_bs128_declr_nodpo_useresponse_iter_1 | null | [
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|
# 0.001_3iters_bs128_declr_nodpo_useresponse_iter_1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More informa... | [
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text-generation | transformers |
# Model Card for alokabhishek/Meta-Llama-3-8B-Instruct-bnb-8bit
<!-- Provide a quick summary of what the model is/does. -->
This repo contains 8-bit quantized (using bitsandbytes) model of Meta's Meta-Llama-3-8B-Instruct
## Model Details
- Model creator: [Meta](https://huggingface.co/meta-llama)
- Original model: ... | {"license": "other", "library_name": "transformers", "tags": ["8bit", "bnb", "bitsandbytes", "llama", "llama-3", "facebook", "meta", "8b", "quantized"], "license_name": "llama3", "license_link": "LICENSE", "pipeline_tag": "text-generation"} | alokabhishek/Meta-Llama-3-8B-Instruct-bnb-8bit | null | [
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| Model Card for alokabhishek/Meta-Llama-3-8B-Instruct-bnb-8bit
=============================================================
This repo contains 8-bit quantized (using bitsandbytes) model of Meta's Meta-Llama-3-8B-Instruct
Model Details
-------------
* Model creator: Meta
* Original model: Meta-Llama-3-8B-Instruct
... | [
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text-generation | transformers |
# Uploaded model
- **Developed by:** wallaceblaia
- **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/un... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "sft"], "base_model": "unsloth/mistral-7b-bnb-4bit"} | wallaceblaia/mistral-icm-04 | null | [
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|
# Uploaded model
- Developed by: wallaceblaia
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
<img src="URL width="200"/>
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text-generation | transformers |
<!-- 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. -->
# safe-spin-iter2
This model is a fine-tuned version of [AmberYifan/safe-spin-iter1](https://huggingface.co/AmberYifan/safe-spin-i... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "AmberYifan/safe-spin-iter1", "model-index": [{"name": "safe-spin-iter2", "results": []}]} | AmberYifan/safe-spin-iter2 | null | [
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|
# safe-spin-iter2
This model is a fine-tuned version of AmberYifan/safe-spin-iter1 on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamete... | [
"# safe-spin-iter2\n\nThis model is a fine-tuned version of AmberYifan/safe-spin-iter1 on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",... | [
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null | null | ## dolphin-llama-3-8b-llamafile-nonAVX
llamafile lets you distribute and run LLMs with a single file. [announcement blog post](https://hacks.mozilla.org/2023/11/introducing-llamafile/)
#### Downloads
- [dolphin-2.9-llama3-8b.Q4_0.llamafile](https://huggingface.co/blueprintninja/dolphin-llama-3-8b-llamafile-nonAVX/r... | {"tags": ["llamafile", "GGUF"], "base_model": "QuantFactory/dolphin-2.9-llama3-8b-GGUF"} | blueprintninja/dolphin-llama-3-8b-llamafile-nonAVX | null | [
"llamafile",
"GGUF",
"base_model:QuantFactory/dolphin-2.9-llama3-8b-GGUF",
"region:us"
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#llamafile #GGUF #base_model-QuantFactory/dolphin-2.9-llama3-8b-GGUF #region-us
| ## dolphin-llama-3-8b-llamafile-nonAVX
llamafile lets you distribute and run LLMs with a single file. announcement blog post
#### Downloads
- dolphin-2.9-llama3-8b.Q4_0.llamafile
This repository was created using the llamafile-builder
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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. -->
# my_zh_CN_asr_cv13_model
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice_13_0"], "metrics": ["wer", "cer"], "base_model": "jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn", "model-index": [{"name": "my_zh_CN_asr_cv13_model", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Auto... | tristayqc/my_zh_CN_asr_cv13_model | null | [
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"license:apache-2.0",
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| my\_zh\_CN\_asr\_cv13\_model
============================
This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn on the common\_voice\_13\_0 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1614
* Cer: 0.0674
* Wer: 0.375
Model description
------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
weighted/imatrix quants of https://huggingface.co/SparseLLM/ReluLLaMA-70B
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/ReluLLaMA-70B-GGU... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "base_model": "SparseLLM/ReluLLaMA-70B", "quantized_by": "mradermacher"} | mradermacher/ReluLLaMA-70B-i1-GGUF | null | [
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"en"
] | TAGS
#transformers #gguf #en #base_model-SparseLLM/ReluLLaMA-70B #license-llama2 #endpoints_compatible #region-us
| About
-----
weighted/imatrix quants of URL
static quants are available at URL
Usage
-----
If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.
Provided Quants
---------------
(sorted by size, not necessarily quality. ... | [] | [
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text-to-image | diffusers |
# 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 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
... | {"library_name": "diffusers"} | rubbrband/LahHongchenSDXLSD15_sd15V10 | null | [
"diffusers",
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"1910.09700"
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#diffusers #safetensors #arxiv-1910.09700 #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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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. -->
# GUE_prom_prom_core_all-seqsight_4096_512_27M-L1_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_27M... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_core_all-seqsight_4096_512_27M-L1_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_core_all-seqsight_4096_512_27M-L1_f | null | [
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"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_core\_all-seqsight\_4096\_512\_27M-L1\_f
=========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_core\_all dataset.
It achieves the following results on the evaluation set:
*... | [
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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. -->
# GUE_prom_prom_300_notata-seqsight_4096_512_27M-L8_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_2... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_4096_512_27M-L8_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_4096_512_27M-L8_f | null | [
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_4096\_512\_27M-L8\_f
===========================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation se... | [
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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. -->
# GUE_prom_prom_300_notata-seqsight_4096_512_27M-L32_f
This model is a fine-tuned version of [mahdibaghbanzadeh/seqsight_4096_512_... | {"library_name": "peft", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "mahdibaghbanzadeh/seqsight_4096_512_27M", "model-index": [{"name": "GUE_prom_prom_300_notata-seqsight_4096_512_27M-L32_f", "results": []}]} | mahdibaghbanzadeh/GUE_prom_prom_300_notata-seqsight_4096_512_27M-L32_f | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:mahdibaghbanzadeh/seqsight_4096_512_27M",
"region:us"
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#peft #safetensors #generated_from_trainer #base_model-mahdibaghbanzadeh/seqsight_4096_512_27M #region-us
| GUE\_prom\_prom\_300\_notata-seqsight\_4096\_512\_27M-L32\_f
============================================================
This model is a fine-tuned version of mahdibaghbanzadeh/seqsight\_4096\_512\_27M on the mahdibaghbanzadeh/GUE\_prom\_prom\_300\_notata dataset.
It achieves the following results on the evaluation ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* training\\_steps: 10000",
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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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width... | {"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "microsoft/Phi-3-mini-4k-instruct", "model-index": [{"name": "phi-3-mini-legal-ift", "results": []}]} | prithviraj-maurya/phi-3-mini-legal-ift | null | [
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|
<img src="URL alt="Visualize in Weights & Biases" width="200" height="32"/>
# phi-3-mini-legal-ift
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and ev... | [
"# phi-3-mini-legal-ift\n\nThis model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset.",
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"## Training and evaluation data\n\nMore information needed",
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text-generation | transformers | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Mod... | {"license": "gemma", "library_name": "transformers", "tags": ["merge"], "base_model": ["google/gemma-1.1-2b-it", "google/gemma-2b"]} | lemon-mint/gemma-2b-diff-model | null | [
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| # Model Card for Model ID
This modelcard aims to be a base template for new models. It has been generated using this raw template.
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- Language(s) (NLP):
- License:
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text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-portuguese-cased-finetuned-RM-4
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "neuralmind/bert-base-portuguese-cased", "model-index": [{"name": "bert-base-portuguese-cased-finetuned-RM-4", "results": []}]} | ricigl/bert-base-portuguese-cased-finetuned-RM-4 | null | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-generation",
"generated_from_trainer",
"base_model:neuralmind/bert-base-portuguese-cased",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-25T23:52:26+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #bert #text-generation #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us
| bert-base-portuguese-cased-finetuned-RM-4
=========================================
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1086
Model description
-----------------
More information need... | [
"### 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: 20",
"### Trainin... | [
"TAGS\n#transformers #tensorboard #safetensors #bert #text-generation #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n... | [
56,
101,
5,
44
] | [
"TAGS\n#transformers #tensorboard #safetensors #bert #text-generation #generated_from_trainer #base_model-neuralmind/bert-base-portuguese-cased #license-mit #autotrain_compatible #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* lear... |
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