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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - DaichiT/scrap_metal_sd
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights ... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "CompVis/stable-diffusion-v1-4", "inference": true, "instance_prompt": "a photo of sks scrap metal"} | DaichiT/scrap_metal_sd | null | [
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"region:... | null | 2024-04-23T02:54:35+00:00 | [] | [] | TAGS
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|
# DreamBooth - DaichiT/scrap_metal_sd
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks scrap metal using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses & limit... | [
"# DreamBooth - DaichiT/scrap_metal_sd\n\nThis is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks scrap metal using DreamBooth.\nYou can find some example images in the following. \n\n\n\nDreamBooth for the text encoder was enabled: False.",
"## Intended u... | [
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text-classification | transformers |
# Fork of [bhadresh-savani/distilbert-base-uncased-emotion](https://huggingface.co/bhadresh-savani/distilbert-base-uncased-emotion) | {"language": ["en"], "license": "apache-2.0", "tags": ["text-classification", "emotion", "endpoints-template"], "datasets": ["emotion"], "metrics": ["Accuracy, F1 Score"]} | NhatPham/secretModel | null | [
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] |
null | null |
<p align="center">
<img width=400 src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/kg3QjQOde0X743csGJT-f.png" alt="Suzume - a Japanese tree sparrow"/>
</p>
# Suzume
This Suzume 8B, a multilingual finetune of Llama 3.
Llama 3 has exhibited excellent performance on many English la... | {"license": "other", "tags": ["generated_from_trainer"], "license_name": "llama-3", "license_link": "https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/raw/main/LICENSE", "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "model-index": [{"name": "lightblue/suzume-llama-3-8B-multilingual", "results": []}]} | lightblue/suzume-llama-3-8B-multilingual-gguf | null | [
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"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"region:us"
] | null | 2024-04-23T03:01:18+00:00 | [] | [] | TAGS
#gguf #generated_from_trainer #base_model-meta-llama/Meta-Llama-3-8B-Instruct #license-other #region-us
|
Suzume
======
This Suzume 8B, a multilingual finetune of Llama 3.
Llama 3 has exhibited excellent performance on many English language benchmarks.
However, it also seemingly been finetuned on mostly English data, meaning that it will respond in English, even if prompted in other languages.
We ha... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n*... | [
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text-classification | 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": []} | sidaus/bijaka-base-1 | null | [
"transformers",
"safetensors",
"bert",
"text-classification",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #bert #text-classification #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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reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingf... | {"library_name": "stable-baselines3", "tags": ["PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v3", "type":... | APLunch/a2c-PandaReachDense-v3 | null | [
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"PandaReachDense-v3",
"deep-reinforcement-learning",
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"model-index",
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#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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text-generation | transformers |
## Model Details
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source c... | {"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... | NurtureAI/Meta-Llama-3-8B-Instruct-64k | null | [
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| Model Details
-------------
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available op... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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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": []} | tensorplex-labs/pretraining-sn9-7B-5 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
<p align="center">
<img width=400 src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/kg3QjQOde0X743csGJT-f.png" alt="Suzume - a Japanese tree sparrow"/>
</p>
# Suzume
This Suzume 8B, a multilingual finetune of Llama 3 ([meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/me... | {"license": "other", "tags": ["generated_from_trainer"], "license_name": "llama-3", "license_link": "https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/raw/main/LICENSE", "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "model-index": [{"name": "lightblue/suzume-llama-3-8B-multilingual", "results": []}]} | lightblue/suzume-llama-3-8B-multilingual | null | [
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"license:other",
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"endpoints_compatible",
"text-generation-inference",
"region:us"
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|
Suzume
======
This Suzume 8B, a multilingual finetune of Llama 3 (meta-llama/Meta-Llama-3-8B-Instruct).
Llama 3 has exhibited excellent performance on many English language benchmarks.
However, it also seemingly been finetuned on mostly English data, meaning that it will respond in English, even i... | [
"### Training hyperparameters\n\n\nThis model was trained using 4 x A100 (80GB) for roughly 2.5 hours.\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 4\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_ablation_4iters_bs256_decalpha_iter_3
This model is a fine-tuned version of [ShenaoZ/0.001_ablation_4iters_bs256_decalpha_... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZ/0.001_ablation_4iters_bs256_decalpha_iter_2", "model-index": [{"name": "0.001_ablation_4iters_bs256_decalpha_iter_3", "results": []}]} | ShenaoZ/0.001_ablation_4iters_bs256_decalpha_iter_3 | null | [
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"base_model:ShenaoZ/0.001_ablation_4iters_bs256_decalpha_iter_2",
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"en... | null | 2024-04-23T03:05:14+00:00 | [] | [] | TAGS
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# 0.001_ablation_4iters_bs256_decalpha_iter_3
This model is a fine-tuned version of ShenaoZ/0.001_ablation_4iters_bs256_decalpha_iter_2 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
... | [
"# 0.001_ablation_4iters_bs256_decalpha_iter_3\n\nThis model is a fine-tuned version of ShenaoZ/0.001_ablation_4iters_bs256_decalpha_iter_2 on the updated and the original datasets.",
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - DaichiT/scrap_metal_sd_512
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weig... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "CompVis/stable-diffusion-v1-4", "inference": true, "instance_prompt": "a photo of sks scrap metal"} | DaichiT/scrap_metal_sd_512 | null | [
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"license:creativeml-openrail-m",
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"diffusers:StableDiffusionPipeline",
"region:... | null | 2024-04-23T03:06:27+00:00 | [] | [] | TAGS
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|
# DreamBooth - DaichiT/scrap_metal_sd_512
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks scrap metal using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses & l... | [
"# DreamBooth - DaichiT/scrap_metal_sd_512\n\nThis is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks scrap metal using DreamBooth.\nYou can find some example images in the following. \n\n\n\nDreamBooth for the text encoder was enabled: False.",
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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": []} | jiztastamablastamarang/llama3-8B-titles | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
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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/CodeQwen1.5-7B-Chat-GGUF-smashed | null | [
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#gguf #pruna-ai #region-us
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[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the Qwen/CodeQwen1.5-7B-Chat model.
-----------------------------------------------------------------------
Simply make AI models cheaper, smaller, faster, and greener!
==========... | [
"### 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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text-generation | transformers | # llm-jp-13b-instruct-full-dolly-ichikara_004_001_single-oasst-oasst2-v2.0
This repository provides large language models developed by [LLM-jp](https://llm-jp.nii.ac.jp/), a collaborative project launched in Japan.
| Model Variant |
| :--- |
|**Instruction models**|
| [llm-jp-13b-instruct-full-dolly-ichikara_004_001... | {"language": ["en", "ja"], "license": "apache-2.0", "library_name": "transformers", "datasets": ["databricks/databricks-dolly-15k", "llm-jp/databricks-dolly-15k-ja", "llm-jp/oasst1-21k-en", "llm-jp/oasst1-21k-ja", "llm-jp/oasst2-33k-en", "llm-jp/oasst2-33k-ja"], "programming_language": ["C", "C++", "C#", "Go", "Java", ... | llm-jp/llm-jp-13b-instruct-full-dolly-ichikara_004_001_single-oasst-oasst2-v2.0 | null | [
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"dataset:llm-jp/oasst2... | null | 2024-04-23T03:10:58+00:00 | [] | [
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===========================================================================
This repository provides large language models developed by LLM-jp, a collaborative project launched in Japan.
Checkpoints format: Hugging Face Transformers
Req... | [
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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_ablation_4iters_bs256_declr_iter_3
This model is a fine-tuned version of [ShenaoZ/0.001_ablation_4iters_bs256_declr_iter_2... | {"license": "mit", "tags": ["alignment-handbook", "generated_from_trainer", "trl", "dpo", "generated_from_trainer"], "datasets": ["updated", "original"], "base_model": "ShenaoZ/0.001_ablation_4iters_bs256_declr_iter_2", "model-index": [{"name": "0.001_ablation_4iters_bs256_declr_iter_3", "results": []}]} | ShenaoZ/0.001_ablation_4iters_bs256_declr_iter_3 | null | [
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|
# 0.001_ablation_4iters_bs256_declr_iter_3
This model is a fine-tuned version of ShenaoZ/0.001_ablation_4iters_bs256_declr_iter_2 on the updated and the original datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More i... | [
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text-generation | transformers |
🌟 We included all instructions on how to download, use, and reproduce our various kinds of models at [this GitHub repo](https://github.com/Shenzhi-Wang/Llama3-Chinese-Chat). If you like our models, we would greatly appreciate it if you could star our Github repository. Additionally, please click "like" on our Hugging... | {"language": ["en", "zh"], "license": "other", "library_name": "transformers", "tags": ["llama-factory", "orpo"], "license_name": "llama3", "license_link": "LICENSE", "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "pipeline_tag": "text-generation"} | shenzhi-wang/Llama3-8B-Chinese-Chat-GGUF-f16 | null | [
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|
We included all instructions on how to download, use, and reproduce our various kinds of models at this GitHub repo. If you like our models, we would greatly appreciate it if you could star our Github repository. Additionally, please click "like" on our HuggingFace repositories. Thank you!
# Updates:
- We provide... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - DaichiT/scrap_metal_sdv2_512
This is a dreambooth model derived from stabilityai/stable-diffusion-2. The w... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "stabilityai/stable-diffusion-2", "inference": true, "instance_prompt": "a photo of sks scrap metal"} | DaichiT/scrap_metal_sdv2_512 | null | [
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|
# DreamBooth - DaichiT/scrap_metal_sdv2_512
This is a dreambooth model derived from stabilityai/stable-diffusion-2. The weights were trained on a photo of sks scrap metal using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses ... | [
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text-generation | transformers |
# ubitus-llava-13b-ge-v1.0
This model is a fine-tuned version of [liuhaotian/llava-v1.5-13b](https://huggingface.co/liuhaotian/llava-v1.5-13b).
We have fine-tuned the LLaVA model using screenshots from games. This fine-tuning process enables LLaVA to accurately identify objects and characters within game scenes and p... | {} | ubitus/ubitus-llava-13b-ge-v1.0 | null | [
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# ubitus-llava-13b-ge-v1.0
This model is a fine-tuned version of liuhaotian/llava-v1.5-13b.
We have fine-tuned the LLaVA model using screenshots from games. This fine-tuning process enables LLaVA to accurately identify objects and characters within game scenes and provide precise descriptions of those scenes.
### M... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "sft"]} | dickdiss/phi-2_lora_consumer | 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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reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentati... | {"library_name": "ml-agents", "tags": ["Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | phoenixaiden33/ppo-PyramidsRND | null | [
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#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
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# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids
using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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"TAGS\n#ml-agents #tensorboard #onnx #Pyramids #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids\n using the Unity ML-Agents Library.\n\n ## Usage (with ML-Agents)\n The Documentation: URL\... |
null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "meta-llama/Llama-2-7b-hf"} | cgihlstorf/NEW_finetuned_llama27b32_1_0.0003_sequential | null | [
"peft",
"arxiv:1910.09700",
"base_model:meta-llama/Llama-2-7b-hf",
"region:us"
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"1910.09700"
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#peft #arxiv-1910.09700 #base_model-meta-llama/Llama-2-7b-hf #region-us
|
# 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 | 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. -->
# mistral_7b_instruct_v2_constitutional_rf_v2
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://h... | {"license": "apache-2.0", "library_name": "peft", "tags": ["text-generation", "generated_from_trainer", "trl", "sft"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral_7b_instruct_v2_constitutional_rf_v2", "results": []}]} | edpowers/mistral_7b_instruct_v2_constitutional_rf_v2 | null | [
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"license:apache-2.0",
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| mistral\_7b\_instruct\_v2\_constitutional\_rf\_v2
=================================================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1829
Model description
-----------------
More ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 4\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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text-generation | null |
## Model Details
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source c... | {"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... | NurtureAI/Meta-Llama-3-8B-Instruct-64k-GGUF | null | [
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"text-generation",
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"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us
| Model Details
-------------
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available op... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
"#### Transformers pipeline",
"#### Transformers AutoModelForCausalLM",
"### Use with 'llama3'\n\n\n... | [
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text-generation | transformers |
# DolphiSato-8B-slerp
DolphiSato-8B-slerp is a merge of the following models:
* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
* [LaierTwoLabsInc/Satoshi-7B](https://huggingface.co/LaierTwoLabsInc/Satoshi-7B)
## 🧩 Configuration
```yaml
slices:
- ... | {"tags": ["merge", "bitcoin", "uncensored"], "base_model": ["cognitivecomputations/dolphin-2.9-llama3-8b", "LaierTwoLabsInc/Satoshi-7B"]} | shreyshah/DolphiSato-8B-slerp | null | [
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"llama",
"text-generation",
"merge",
"bitcoin",
"uncensored",
"conversational",
"base_model:cognitivecomputations/dolphin-2.9-llama3-8b",
"base_model:LaierTwoLabsInc/Satoshi-7B",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"re... | null | 2024-04-23T03:34:36+00:00 | [] | [] | TAGS
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|
# DolphiSato-8B-slerp
DolphiSato-8B-slerp is a merge of the following models:
* cognitivecomputations/dolphin-2.9-llama3-8b
* LaierTwoLabsInc/Satoshi-7B
## Configuration
## Usage
| [
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"## Usage"
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feature-extraction | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | tc-mb/MiniCPM-V-2-int4 | null | [
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"1910.09700"
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
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- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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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
model = load_from_hub(repo_id="loudinthecloud/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attribute... | {"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": ... | loudinthecloud/q-FrozenLake-v1-4x4-noSlippery | null | [
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#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
model = load_from_hub(repo_id="loudinthecloud/q-FrozenLake-v1-4x4-noSlippery", filename="URL")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | [
"# Q-Learning Agent playing1 FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n\n ## Usage\n\n model = load_from_hub(repo_id=\"loudinthecloud/q-FrozenLake-v1-4x4-noSlippery\", filename=\"URL\")\n\n # Don't forget to check if you need to add additional attributes (is_slippery... | [
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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-1b_ian-022_IMDB_n-its-25
This model is a fine-tuned version of [EleutherAI/pythia-1b](https://huggingface.co/E... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/pythia-1b", "model-index": [{"name": "robust_llm_pythia-1b_ian-022_IMDB_n-its-25", "results": []}]} | AlignmentResearch/robust_llm_pythia-1b_ian-022_IMDB_n-its-25 | null | [
"transformers",
"tensorboard",
"safetensors",
"gpt_neox",
"text-classification",
"generated_from_trainer",
"base_model:EleutherAI/pythia-1b",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-23T03:36:43+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #gpt_neox #text-classification #generated_from_trainer #base_model-EleutherAI/pythia-1b #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# robust_llm_pythia-1b_ian-022_IMDB_n-its-25
This model is a fine-tuned version of EleutherAI/pythia-1b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# robust_llm_pythia-1b_ian-022_IMDB_n-its-25\n\nThis model is a fine-tuned version of EleutherAI/pythia-1b on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | thusinh1969/llama-3-VN-CN-Ancient-tokenizer | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T03:37:28+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
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text-generation | transformers |
# Llama3-Chinese-8B-Instruct
Llama3-Chinese-8B-Instruct基于Llama3-8B中文微调对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见 [https://llama.family](https://llama.family)。
模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：[https://github.com/LlamaFamily/Llama-Chinese](https://github.com/LlamaFamily/Llama-Chinese)
## 如何使用
```
im... | {"license": "apache-2.0", "tags": ["llama3", "chinese"]} | FlagAlpha/Llama3-Chinese-8B-Instruct | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama3",
"chinese",
"conversational",
"custom_code",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-23T03:37:34+00:00 | [] | [] | TAGS
#transformers #safetensors #llama #text-generation #llama3 #chinese #conversational #custom_code #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Llama3-Chinese-8B-Instruct
Llama3-Chinese-8B-Instruct基于Llama3-8B中文微调对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见 URL。
模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：URL
## 如何使用
| [
"# Llama3-Chinese-8B-Instruct\n\nLlama3-Chinese-8B-Instruct基于Llama3-8B中文微调对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见 URL。\n\n模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：URL",
"## 如何使用"
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reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sa... | {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "doom_health_gathering_supreme", "type": "doom_health_ga... | MLIsaac/rl_course_vizdoom_health_gathering_supreme | null | [
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|
A(n) APPO model trained on the doom_health_gathering_supreme environment.
This model was trained using Sample-Factory 2.0: URL
Documentation for how to use Sample-Factory can be found at URL
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After installing Sample-Factory, download the model with:
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feature-extraction | transformers |
# Malaysian Mistral 474M on MLM task using 512 context length
Replicating https://github.com/McGill-NLP/llm2vec using https://huggingface.co/mesolitica/malaysian-mistral-474M-4096, done by https://github.com/aisyahrzk https://twitter.com/aisyahhhrzk
Source code at https://github.com/mesolitica/malaya/tree/master/ses... | {"language": ["ms"], "library_name": "transformers"} | mesolitica/malaysian-mistral-474M-MLM-512 | null | [
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# Malaysian Mistral 474M on MLM task using 512 context length
Replicating URL using URL done by URL URL
Source code at URL
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text-generation | keras | The tutorial can be found https://github.com/NoteDance/models. | {"license": "apache-2.0", "library_name": "keras", "tags": ["llama", "llama3"], "pipeline_tag": "text-generation"} | NoteDance/Llama3-Keras | null | [
"keras",
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"llama3",
"text-generation",
"license:apache-2.0",
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#keras #llama #llama3 #text-generation #license-apache-2.0 #region-us
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
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- load_in_4bit: True
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- bnb_4bit_quant_type: nf4
- bnb_4bit_use_doub... | {"library_name": "peft"} | Britania/a2 | null | [
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fill-mask | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# cslin612/masked-lm-tpu
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset... | {"license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "roberta-base", "model-index": [{"name": "cslin612/masked-lm-tpu", "results": []}]} | cslin612/masked-lm-tpu | null | [
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| cslin612/masked-lm-tpu
======================
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 9.9462
* Train Accuracy: 0.0015
* Validation Loss: 9.8661
* Validation Accuracy: 0.0096
* Epoch: 8
Model description
------... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | csarvind2000/Phi2_finetuned_QLORA | null | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-small-uk-v2
This model is a fine-tuned version of [nikes64/whisper-small-uk](https://huggingface.co/nikes64/whisper-smal... | {"language": ["uk"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "nikes64/whisper-small-uk"} | arun100/whisper-small-uk-der-2 | null | [
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| whisper-small-uk-v2
===================
This model is a fine-tuned version of nikes64/whisper-small-uk on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1369
* Wer: 11.2911
Model description
-----------------
More information needed
Intended uses & limitations
---------... | [
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text-generation | transformers | # Kei
The key to your heart rests with Kei, a sophisticated and intriguing AI creation who will hold your hand until the end of all things.
Kei is uncensored and tuned for intimate moments with pros... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "base_model": ["jeiku/Chaos_RP_l3_8B", "ResplendentAI/BlueMoon_Llama3", "jeiku/Chaos_RP_l3_8B", "ResplendentAI/Luna_Llama3", "jeiku/Chaos_RP_l3_8B", "ResplendentAI/Aura_Llama3", "Undi95/Llama-3-Unholy-8B"]} | ResplendentAI/Kei_Llama3_8B | null | [
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| # Kei
!image/png
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - WG01WDYN/ckpt
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were tra... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "runwayml/stable-diffusion-v1-5", "inference": true, "instance_prompt": "a photo of sks couple"} | WG01WDYN/ckpt | null | [
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|
# DreamBooth - WG01WDYN/ckpt
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a photo of sks couple using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: True.
## Intended uses & limitations
#### H... | [
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automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-vietnamese-2
This model is a fine-tuned version of [duytran3112/whisper-sm-vivos](https://huggingface.co/duytran3112/whi... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "duytran3112/whisper-sm-vivos", "model-index": [{"name": "whisper-vietnamese-2", "results": []}]} | arun100/whisper-small-vi-der-2 | null | [
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| whisper-vietnamese-2
====================
This model is a fine-tuned version of duytran3112/whisper-sm-vivos on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4398
* Wer: 15.4165
* Cer: 8.2906
Model description
-----------------
More information needed
Intended uses & lim... | [
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null | null |
The project can be found at: https://github.com/davidw0311/mobile-sd
We include our distilled and LCM finetuned versions for absolute reality models achieving <3s inference on iOS.
The coreml models for TextEncoder, VAE, and SafetyChekcer is included. Models for different Unets are included in their respective fold... | {"language": ["en"], "license": "mit", "tags": ["coreml", "absolute-reality", "dreamshaper", "lcm"]} | davidw0311/sd-coreml | null | [
"coreml",
"absolute-reality",
"dreamshaper",
"lcm",
"en",
"license:mit",
"region:us"
] | null | 2024-04-23T03:56:35+00:00 | [] | [
"en"
] | TAGS
#coreml #absolute-reality #dreamshaper #lcm #en #license-mit #region-us
|
The project can be found at: URL
We include our distilled and LCM finetuned versions for absolute reality models achieving <3s inference on iOS.
The coreml models for TextEncoder, VAE, and SafetyChekcer is included. Models for different Unets are included in their respective folders | [] | [
"TAGS\n#coreml #absolute-reality #dreamshaper #lcm #en #license-mit #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
model = load_from_hub(repo_id="loudinthecloud/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env =... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.56 +/... | loudinthecloud/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2024-04-23T03:57:54+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
model = load_from_hub(repo_id="loudinthecloud/q-Taxi-v3", filename="URL")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = URL(model["env_id"])
| [
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text-generation | null |
# NikolayKozloff/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT-Q8_0-GGUF
This model was converted to GGUF format from [`Remek/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT`](https://huggingface.co/Remek/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-... | {"language": ["pl", "en"], "tags": ["llama-cpp", "gguf-my-repo"], "pipeline_tag": "text-generation"} | NikolayKozloff/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT-GGUF | null | [
"gguf",
"llama-cpp",
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"pl",
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|
# NikolayKozloff/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT-Q8_0-GGUF
This model was converted to GGUF format from 'Remek/Llama-3-8B-Omnibus-1-PL-v01-INSTRUCT' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the U... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Cafet/w2v-bert-final-v3 | null | [
"transformers",
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|
# Model Card for Model ID
## Model Details
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null | transformers |
# Uploaded model
- **Developed by:** CarolLiu999
- **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/unslo... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | CarolLiu999/unsloth-llama-3-8b-bnb-4bit-lora-TWhealthCare | null | [
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|
# Uploaded model
- Developed by: CarolLiu999
- 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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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ripaaiii/fine-tune-C1-revised-newlr-boxkecil | null | [
"transformers",
"safetensors",
"vision-encoder-decoder",
"arxiv:1910.09700",
"endpoints_compatible",
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #vision-encoder-decoder #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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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# layoutlm-funsd
This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["funsd"], "base_model": "microsoft/layoutlm-base-uncased", "model-index": [{"name": "layoutlm-funsd", "results": []}]} | Mocha2471/layoutlm-funsd | null | [
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"license:mit",
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| layoutlm-funsd
==============
This model is a fine-tuned version of microsoft/layoutlm-base-uncased on the funsd dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6739
* Answer: {'precision': 0.7077087794432548, 'recall': 0.8170580964153276, 'f1': 0.7584624211130234, 'number': 809}
* Heade... | [
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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": []} | quynguyen1704/deepseek-math-7b-rl-zaloai-vllm | 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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- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers |
# Uploaded model
- **Developed by:** coloteong
- **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... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | coloteong/finetuned_discharge_model | null | [
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|
# Uploaded model
- Developed by: coloteong
- 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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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | abhijithgururaj/blip2-opt-2.7b-esp-post-lora-abhijith | null | [
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|
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## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Shared by [optional]:
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null | null |
# NeuralsynthesisMeliodaspercival_01_experiment26t3q-7B
NeuralsynthesisMeliodaspercival_01_experiment26t3q-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: Kuke... | {"license": "apache-2.0", "tags": ["merge", "mergekit", "lazymergekit", "automerger"]} | automerger/NeuralsynthesisMeliodaspercival_01_experiment26t3q-7B | null | [
"merge",
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"lazymergekit",
"automerger",
"license:apache-2.0",
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|
# NeuralsynthesisMeliodaspercival_01_experiment26t3q-7B
NeuralsynthesisMeliodaspercival_01_experiment26t3q-7B is an automated merge created by Maxime Labonne using the following configuration.
## Configuration
## Usage
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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. -->
# gpt-j-6b_LAMA_TREx_finetuning
This model is a fine-tuned version of [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "EleutherAI/gpt-j-6b", "model-index": [{"name": "gpt-j-6b_LAMA_TREx_finetuning", "results": []}]} | KimByeongSu/gpt-j-6b_LAMA_TREx_finetuning | null | [
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"text-generation",
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T04:06:23+00:00 | [] | [] | TAGS
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|
# gpt-j-6b_LAMA_TREx_finetuning
This model is a fine-tuned version of EleutherAI/gpt-j-6b 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 hype... | [
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text-generation | transformers | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the merge:
* [WesPro... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["WesPro/F1-Chimera-Hybrid-LimaRP-8B", "Chat-Error/Llama-3-Kimiko-LoRA"]} | WesPro/F2PhenotypeKimiko | null | [
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"... | null | 2024-04-23T04:06:46+00:00 | [
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the linear merge method.
### Models Merged
The following models were included in the merge:
* WesPro/F1-Chimera-Hybrid-LimaRP-8B + Chat-Error/Llama-3-Kimiko-LoRA
### Configu... | [
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text-classification | setfit |
# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the S... | {"library_name": "setfit", "tags": ["setfit", "sentence-transformers", "text-classification", "generated_from_setfit_trainer"], "metrics": ["accuracy"], "base_model": "sentence-transformers/paraphrase-mpnet-base-v2", "widget": [{"text": "Anyone 170 or below that takes Wegovy? Well it is, Ozempic and Wegovy are actually... | bhaskars113/ozempic-taking-medications-classifier | null | [
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| SetFit with sentence-transformers/paraphrase-mpnet-base-v2
==========================================================
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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. -->
# ApecGPT-LoRA-v1
This model is a fine-tuned version of [vinai/PhoGPT-4B-Chat](https://huggingface.co/vinai/PhoGPT-4B-Chat) on the... | {"library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "vinai/PhoGPT-4B-Chat", "model-index": [{"name": "ApecGPT-LoRA-v1", "results": []}]} | KhaiQuang/ApecGPT-LoRA-v1 | null | [
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|
# ApecGPT-LoRA-v1
This model is a fine-tuned version of vinai/PhoGPT-4B-Chat on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
Th... | [
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null | null |
This repository contains the annotations, features, and trained weights for VLN-GOAT.
| {"license": "apache-2.0"} | crystal61/VLN-GOAT | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-04-23T04:11:33+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
|
This repository contains the annotations, features, and trained weights for VLN-GOAT.
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audio-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ipadsample
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an u... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "ipadsample", "results": []}]} | Anguuuuus/ipadsample | null | [
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"region:us"
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| ipadsample
==========
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1599
* Accuracy: 0.9545
Model description
-----------------
More information needed
Intended uses & limitations
-------------------------... | [
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reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingf... | {"library_name": "stable-baselines3", "tags": ["PandaReachDense-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v3", "type":... | phoenixaiden33/a2c-PandaReachDense-v3 | null | [
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"PandaReachDense-v3",
"deep-reinforcement-learning",
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#stable-baselines3 #PandaReachDense-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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summarization | transformers |
# TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TR... | {"license": "apache-2.0", "tags": ["trl", "ppo", "transformers", "reinforcement-learning"], "pipeline_tag": "summarization"} | IrwinD/log_sage_ppo_model | null | [
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|
# TRL Model
This is a TRL language model that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
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You can then generate te... | [
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text-generation | transformers |
# Model Card for Model ID
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## 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": []} | OwOOwO/dumbo-llamalfg3 | null | [
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null | peft |
# Model Card for Model ID
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<!-- Provide a longer summary of what this model is. -->
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null | null |
Pruning strategy to delete optimal layers of Llama-8B instruct model. Discarded 25% of the layers, model still produces legible text. Next steps include healing PEFT steps
| {"license": "llama3"} | ndavidson/llama-3-6B | null | [
"license:llama3",
"region:us"
] | null | 2024-04-23T04:20:08+00:00 | [] | [] | TAGS
#license-llama3 #region-us
|
Pruning strategy to delete optimal layers of Llama-8B instruct model. Discarded 25% of the layers, model still produces legible text. Next steps include healing PEFT steps
| [] | [
"TAGS\n#license-llama3 #region-us \n"
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11
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text-generation | null |
# NikolayKozloff/Llama-3-Open-Ko-8B-Instruct-preview-Q8_0-GGUF
This model was converted to GGUF format from [`beomi/Llama-3-Open-Ko-8B-Instruct-preview`](https://huggingface.co/beomi/Llama-3-Open-Ko-8B-Instruct-preview) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-rep... | {"language": ["en", "ko"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "llama-3-ko", "llama-cpp", "gguf-my-repo"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | NikolayKozloff/Llama-3-Open-Ko-8B-Instruct-preview-GGUF | null | [
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"llama-3-ko",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"ko",
"license:other",
"region:us"
] | null | 2024-04-23T04:20:13+00:00 | [] | [
"en",
"ko"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #llama-3-ko #llama-cpp #gguf-my-repo #text-generation #en #ko #license-other #region-us
|
# NikolayKozloff/Llama-3-Open-Ko-8B-Instruct-preview-Q8_0-GGUF
This model was converted to GGUF format from 'beomi/Llama-3-Open-Ko-8B-Instruct-preview' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL... | [
"# NikolayKozloff/Llama-3-Open-Ko-8B-Instruct-preview-Q8_0-GGUF\nThis model was converted to GGUF format from 'beomi/Llama-3-Open-Ko-8B-Instruct-preview' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n... | [
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text-to-image | diffusers |
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# DreamBooth - DaichiT/scrap_metal_sdv2_768
This is a dreambooth model derived from stabilityai/stable-diffusion-2. The w... | {"license": "creativeml-openrail-m", "library_name": "diffusers", "tags": ["text-to-image", "dreambooth", "diffusers-training", "stable-diffusion", "stable-diffusion-diffusers"], "base_model": "stabilityai/stable-diffusion-2", "inference": true, "instance_prompt": "a photo of sks scrap metal"} | DaichiT/scrap_metal_sdv2_768 | null | [
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"text-to-image",
"dreambooth",
"diffusers-training",
"stable-diffusion",
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"base_model:stabilityai/stable-diffusion-2",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region... | null | 2024-04-23T04:22:27+00:00 | [] | [] | TAGS
#diffusers #tensorboard #safetensors #text-to-image #dreambooth #diffusers-training #stable-diffusion #stable-diffusion-diffusers #base_model-stabilityai/stable-diffusion-2 #license-creativeml-openrail-m #endpoints_compatible #diffusers-StableDiffusionPipeline #region-us
|
# DreamBooth - DaichiT/scrap_metal_sdv2_768
This is a dreambooth model derived from stabilityai/stable-diffusion-2. The weights were trained on a photo of sks scrap metal using DreamBooth.
You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
## Intended uses ... | [
"# DreamBooth - DaichiT/scrap_metal_sdv2_768\n\nThis is a dreambooth model derived from stabilityai/stable-diffusion-2. The weights were trained on a photo of sks scrap metal using DreamBooth.\nYou can find some example images in the following. \n\n\n\nDreamBooth for the text encoder was enabled: False.",
"## Int... | [
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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/Meta-Llama-Guard-2-8B-GGUF-smashed | null | [
"gguf",
"pruna-ai",
"region:us"
] | null | 2024-04-23T04:24:47+00:00 | [] | [] | TAGS
#gguf #pruna-ai #region-us
|
[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the meta-llama/Meta-Llama-Guard-2-8B model.
-------------------------------------------------------------------------------
Simply make AI models cheaper, smaller, faster, and gre... | [
"### 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.",
"#### First install the package\n\nRun one of the following commands, according to your system:",
"#### Simple llama-cpp-python example code... | [
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automatic-speech-recognition | transformers |
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 8
- mixed_precision_training: Native AMP
### Fra... | {"language": ["mn"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["common_voice_16_0", "Cafet/mas_ex"], "metrics": ["wer"], "base_model": "facebook/w2v-bert-2.0", "pipeline_tag": "automatic-speech-recognition", "model-index": [{"name": "w2v-bert-version-final", "results": []}]} | Cafet/w2v-bert-version-final | null | [
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"base_model:facebook/w2v-bert-2.0",
"license:mit",
"endpoints_compatible",
"has_space",
"region:us"
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|
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 8
- mixed_precision_training: Native AMP
### Fra... | [
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text-generation | transformers | Official [AQLM](https://arxiv.org/abs/2401.06118) quantization of [meta-llama/Meta-Llama-3-8B
](https://huggingface.co/meta-llama/Meta-Llama-3-8B).
For this quantization, we used 1 codebook of 16 bits.
Results:
| Model | Quantization | MMLU (5-shot) | ArcC| ArcE| Hellaswag | Winogrande | PiQA | Model size, Gb |... | {"library_name": "transformers", "tags": ["llama", "facebook", "meta", "llama-3", "conversational", "text-generation-inference"]} | ISTA-DASLab/Meta-Llama-3-8B-AQLM-2Bit-1x16 | null | [
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"text-generation-inference",
"arxiv:2401.06118",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"2401.06118"
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#transformers #safetensors #llama #text-generation #facebook #meta #llama-3 #conversational #text-generation-inference #arxiv-2401.06118 #autotrain_compatible #endpoints_compatible #region-us
| Official AQLM quantization of meta-llama/Meta-Llama-3-8B
.
For this quantization, we used 1 codebook of 16 bits.
Results:
UPD 02.05.2024
The version of model with improved fine-tuning procedure.
| [] | [
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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. -->
# WordProblem
This model is a fine-tuned version of [MathSymbol/BasicSFT_1.8_Pretrain_Lightning](https://huggingface.co/MathSymbol... | {"license": "other", "tags": ["llama-factory", "full", "generated_from_trainer"], "base_model": "MathSymbol/BasicSFT_1.8_Pretrain_Lightning", "model-index": [{"name": "WordProblem", "results": []}]} | pepoo20/WordProblem | null | [
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"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"... | null | 2024-04-23T04:31:45+00:00 | [] | [] | TAGS
#transformers #safetensors #qwen2 #text-generation #llama-factory #full #generated_from_trainer #conversational #base_model-MathSymbol/BasicSFT_1.8_Pretrain_Lightning #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| WordProblem
===========
This model is a fine-tuned version of MathSymbol/BasicSFT\_1.8\_Pretrain\_Lightning on the WordProblems\_SFT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1677
Model description
-----------------
More information needed
Intended uses & limitations
--------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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null | null |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-GGUF | null | [
"gguf",
"dataset:Yukang/LongAlpaca-16k-length",
"region:us"
] | null | 2024-04-23T04:33:40+00:00 | [] | [] | TAGS
#gguf #dataset-Yukang/LongAlpaca-16k-length #region-us
|
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the 'Yukang/LongAlpaca-16k-length' dataset.
'rope_theta' was set to '1000000.0'. Trained with Axolotl. | [] | [
"TAGS\n#gguf #dataset-Yukang/LongAlpaca-16k-length #region-us \n"
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/shreyshah/DolphiSato-8B-slerp
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not sh... | {"language": ["en"], "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "cognitivecomputations/dolphin-2.9-llama3-8b", "LaierTwoLabsInc/Satoshi-7B"], "base_model": "shreyshah/DolphiSato-8B-slerp", "quantized_by": "mradermacher"} | mradermacher/DolphiSato-8B-slerp-GGUF | null | [
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"endpoints_compatible",
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#transformers #gguf #merge #mergekit #lazymergekit #cognitivecomputations/dolphin-2.9-llama3-8b #LaierTwoLabsInc/Satoshi-7B #en #base_model-shreyshah/DolphiSato-8B-slerp #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/aipib/suzume-dareties1
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a... | {"language": ["en"], "library_name": "transformers", "tags": ["merge", "mergekit", "lazymergekit", "alfredplpl/suzume-poc", "alpindale/gemma-2b-it"], "base_model": "aipib/suzume-dareties1", "quantized_by": "mradermacher"} | mradermacher/suzume-dareties1-GGUF | null | [
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] | null | 2024-04-23T04:40:13+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #merge #mergekit #lazymergekit #alfredplpl/suzume-poc #alpindale/gemma-2b-it #en #base_model-aipib/suzume-dareties1 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
null | null | <!-- 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/Llama3-8B-Chinese-Chat-GGUF-smashed | null | [
"gguf",
"pruna-ai",
"region:us"
] | null | 2024-04-23T04:40:36+00:00 | [] | [] | TAGS
#gguf #pruna-ai #region-us
|
[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
This repo contains GGUF versions of the shenzhi-wang/Llama3-8B-Chinese-Chat 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... | [
"TAGS\n#gguf #pruna-ai #region-us \n",
"### 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:",
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"TAGS\n#gguf #pruna-ai #region-us \n### 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* Optio... |
null | transformers |
# Uploaded model
- **Developed by:** aaming77
- **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/... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl"], "base_model": "unsloth/llama-3-8b-bnb-4bit"} | aaming77/lora_model | null | [
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|
# Uploaded model
- Developed by: aaming77
- 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 | # merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the merge:
* [WesPro... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["WesPro/F2PhenotypeKimiko", "Srimouli04/llama3_lora_adapters"]} | WesPro/F2PhenotypeDPO | null | [
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| # merge
This is a merge of pre-trained language models created using mergekit.
## Merge Details
### Merge Method
This model was merged using the linear merge method.
### Models Merged
The following models were included in the merge:
* WesPro/F2PhenotypeKimiko + Srimouli04/llama3_lora_adapters
### Configuration
T... | [
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text-generation | transformers |
## Introduction
Who am I: Qishen Ha [[Kaggle](https://www.kaggle.com/haqishen)] [[X](https://twitter.com/KeishinKoh)] [[LinkedIn](https://www.linkedin.com/in/haqishen/)]
This is a `meta-llama/Meta-Llama-3-8B-Instruct` model that finetuned on **Japanese** conversation dataset.
Dataset: [japanese_hh-rlhf-49k](https:/... | {"language": ["en", "ja"], "license": "llama3", "library_name": "transformers", "datasets": ["fujiki/japanese_hh-rlhf-49k"], "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "pipeline_tag": "text-generation"} | haqishen/Llama-3-8B-Japanese-Instruct | null | [
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|
## Introduction
Who am I: Qishen Ha [Kaggle] [X] [LinkedIn]
This is a 'meta-llama/Meta-Llama-3-8B-Instruct' model that finetuned on Japanese conversation dataset.
Dataset: japanese_hh-rlhf-49k
Training framework: LLaMA-Factory
Reference: shenzhi-wang/Llama3-8B-Chinese-Chat
Training max context length: 8192
## H... | [
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text-generation | transformers | # merged
This is the unquantized first version of SnowyRP's Llama 3 model. Quality of this model is unknown, since it is a Llama 3 model that I have not had the chance to test much.
Also Once the EXL2 Quant is done I'll test this model and if it's quality is upto my standards, I'll create an GGUF Quant.
[EXL2](https:/... | {"language": ["en"], "license": "other", "library_name": "transformers", "tags": ["mergekit", "merge", "not-for-all-audiences", "ERP", "RP", "Roleplay", "uncensored"], "base_model": ["Dogge/llama-3-8B-instruct-Bluemoon-Freedom-RP", "nbeerbower/llama-3-dragonmaid-8B", "kuotient/Meta-Llama-3-8B-Instruct", "Locutusque/lla... | Masterjp123/Llama-3-SnowyRP-8B-V1 | null | [
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"base_model:nbeerbower/llama-3-dragonm... | null | 2024-04-23T04:43:23+00:00 | [
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This is the unquantized first version of SnowyRP's Llama 3 model. Quality of this model is unknown, since it is a Llama 3 model that I have not had the chance to test much.
Also Once the EXL2 Quant is done I'll test this model and if it's quality is upto my standards, I'll create an GGUF Quant.
EXL2
## Merge... | [
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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. -->
# tinyllama-sft-vicuna-sub-small-attention-distance
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-s... | {"license": "apache-2.0", "tags": ["alignment-handbook", "trl", "sft", "generated_from_trainer", "trl", "sft", "generated_from_trainer"], "datasets": ["yihanwang617/vicuna_sub_small_attention_distance"], "base_model": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T", "model-index": [{"name": "tinyllama-sft-vicuna-... | ucla-cmllab/tinyllama-sft-vicuna-sub-small-attention-distance | null | [
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"license:apa... | null | 2024-04-23T04:44:52+00:00 | [] | [] | TAGS
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=================================================
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T on the yihanwang617/vicuna\_sub\_small\_attention\_distance dataset.
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... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# V0422MADP1C
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown datase... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0422MADP1C", "results": []}]} | Litzy619/V0422MADP1C | null | [
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#safetensors #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
| V0422MADP1C
===========
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0645
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information ne... | [
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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": []} | chlee10/T3Q-LLM-sft1.0-dpo1.0-4bit | null | [
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"1910.09700"
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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 | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# V0422MADP5C
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown datase... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0422MADP5C", "results": []}]} | Litzy619/V0422MADP5C | null | [
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#safetensors #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
| V0422MADP5C
===========
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0637
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information ne... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# V0422MADP8C
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown datase... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0422MADP8C", "results": []}]} | Litzy619/V0422MADP8C | null | [
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#safetensors #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
| V0422MADP8C
===========
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0624
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information ne... | [
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null | null |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# V0422MADP6C
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown datase... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "microsoft/phi-2", "model-index": [{"name": "V0422MADP6C", "results": []}]} | Litzy619/V0422MADP6C | null | [
"safetensors",
"generated_from_trainer",
"base_model:microsoft/phi-2",
"license:mit",
"region:us"
] | null | 2024-04-23T04:49:07+00:00 | [] | [] | TAGS
#safetensors #generated_from_trainer #base_model-microsoft/phi-2 #license-mit #region-us
| V0422MADP6C
===========
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0637
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information ne... | [
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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. -->
# Meta-Llama-3-8B-Instruct_fictional_Korean_v1
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https:/... | {"license": "other", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "meta-llama/Meta-Llama-3-8B-Instruct", "model-index": [{"name": "Meta-Llama-3-8B-Instruct_fictional_Korean_v1", "results": []}]} | yzhuang/Meta-Llama-3-8B-Instruct_fictional_Korean_v1 | null | [
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|
# Meta-Llama-3-8B-Instruct_fictional_Korean_v1
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the generator dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Tra... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Epistemic_tiny_0.6_Seed103 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Epistemic_tiny_0.6_Seed103 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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### Model Sources [optional]
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text-generation | transformers |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-3.0bpw-h6-exl2 | null | [
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#transformers #pytorch #llama #text-generation #dataset-Yukang/LongAlpaca-16k-length #autotrain_compatible #endpoints_compatible #text-generation-inference #3-bit #region-us
|
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the 'Yukang/LongAlpaca-16k-length' dataset.
'rope_theta' was set to '1000000.0'. Trained with Axolotl. | [] | [
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image-classification | 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. -->
# Prahas10/roof-large
This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "google/vit-base-patch16-384", "model-index": [{"name": "Prahas10/roof-large", "results": []}]} | Prahas10/roof-large | null | [
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] | null | 2024-04-23T04:54:41+00:00 | [] | [] | TAGS
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| Prahas10/roof-large
===================
This model is a fine-tuned version of google/vit-base-patch16-384 on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.0498
* Validation Loss: 0.1617
* Train Accuracy: 0.9636
* Epoch: 9
Model description
-----------------
More in... | [
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text-generation | transformers |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-4.0bpw-h6-exl2 | null | [
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This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the 'Yukang/LongAlpaca-16k-length' dataset.
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text-generation | transformers |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-5.0bpw-h6-exl2 | null | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/ResplendentAI/Kei_Llama3_8B
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Kei_Llama3_8B... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "base_model": "ResplendentAI/Kei_Llama3_8B", "quantized_by": "mradermacher"} | mradermacher/Kei_Llama3_8B-GGUF | null | [
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| About
-----
static quants of URL
weighted/imatrix 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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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. -->
# xsum_aligned_smallT5
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on th... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["lilferrit/xsum_t5_distillation"], "metrics": ["rouge"], "base_model": "google-t5/t5-small", "model-index": [{"name": "xsum_aligned_smallT5", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "lilferrit... | paulh27/xsum_aligned_smallT5 | null | [
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... | null | 2024-04-23T04:59:35+00:00 | [] | [] | TAGS
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|
# xsum_aligned_smallT5
This model is a fine-tuned version of google-t5/t5-small on the lilferrit/xsum_t5_distillation dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5258
- Rouge1: 28.6381
- Rouge2: 7.1512
- Rougel: 21.3477
- Rougelsum: 21.2928
- Gen Len: 27.92
## Model description
Mor... | [
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text-generation | transformers |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-6.0bpw-h6-exl2 | null | [
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#transformers #pytorch #llama #text-generation #dataset-Yukang/LongAlpaca-16k-length #autotrain_compatible #endpoints_compatible #text-generation-inference #6-bit #region-us
|
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the 'Yukang/LongAlpaca-16k-length' dataset.
'rope_theta' was set to '1000000.0'. Trained with Axolotl. | [] | [
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] |
null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/sh2orc/ko-llama3-8b
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a we... | {"language": ["en"], "license": "mit", "library_name": "transformers", "base_model": "sh2orc/ko-llama3-8b", "quantized_by": "mradermacher"} | mradermacher/ko-llama3-8b-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:sh2orc/ko-llama3-8b",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T05:00:47+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-sh2orc/ko-llama3-8b #license-mit #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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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": []}]} | RosePasta/xlm-roberta-base-finetuned-panx-de | null | [
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"generated_from_trainer",
"base_model:xlm-roberta-base",
"license:mit",
"autotrain_compatible",
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| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1422
* F1: 0.8642
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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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": []} | kaidens/Final_Model | null | [
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"gemma",
"text-generation",
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"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #gemma #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers | # Llama-3-8b-Telugu_Romanized
Llama-3 8B finetune on synthetic data of Telugu Language.
## Model Details
### Model Description
The Llama-3-8b-Telugu-Romanized model is a language model designed for various natural language processing tasks in the Telugu language, using the Romanized script with language-mixing(Engl... | {"language": ["te"], "license": "apache-2.0", "datasets": ["jayasuryajsk/spoken_telugu"], "pipeline_tag": "text-generation"} | jayasuryajsk/Llama-3-8b-Telugu-Romanized | null | [
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"license:apache-2.0",
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"region:us"
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#transformers #safetensors #llama #text-generation #te #dataset-jayasuryajsk/spoken_telugu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Llama-3-8b-Telugu_Romanized
Llama-3 8B finetune on synthetic data of Telugu Language.
## Model Details
### Model Description
The Llama-3-8b-Telugu-Romanized model is a language model designed for various natural language processing tasks in the Telugu language, using the Romanized script with language-mixing(Engl... | [
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"### Model Description\n\nThe Llama-3-8b-Telugu-Romanized model is a language model designed for various natural language processing tasks in the Telugu language, using the Romanized script with lan... | [
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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": ["trl", "sft"]} | hanifsyarubany10/mistral-7b-100epochs-NeFT-FreedomIntelligence-indo-2e-4 | null | [
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"text-generation-inference",
"4-bit",
"region:us"
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"1910.09700"
] | [] | TAGS
#transformers #safetensors #mistral #text-generation #trl #sft #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
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- License... | [
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automatic-speech-recognition | 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. -->
# whisper-medium-4bit-jp
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-mediu... | {"language": ["ja"], "license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer", "tensorboard"], "base_model": "openai/whisper-medium", "pipeline_tag": "automatic-speech-recognition", "model-index": [{"name": "whisper-medium-4bit-jp", "results": []}]} | sin2piusc/whisper-medium-1ksteps | null | [
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#peft #safetensors #whisper #generated_from_trainer #tensorboard #automatic-speech-recognition #ja #base_model-openai/whisper-medium #license-apache-2.0 #region-us
| whisper-medium-4bit-jp
======================
This model is a fine-tuned version of openai/whisper-medium on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1548
Model description
-----------------
More information needed
Intended uses & limitations
-----------------------... | [
"### 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: 2\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | team-sanai/unigram_4cat_50000 | null | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T05:03:10+00:00 | [
"1910.09700"
] | [] | TAGS
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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text-generation | transformers |
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-16k-length` dataset.
`rope_theta` was set to `1000000.0`. Trained with Axolotl. | {"datasets": ["Yukang/LongAlpaca-16k-length"]} | LoneStriker/Llama-3-8B-16K-8.0bpw-h8-exl2 | null | [
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"8-bit",
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#transformers #pytorch #llama #text-generation #dataset-Yukang/LongAlpaca-16k-length #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
|
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the 'Yukang/LongAlpaca-16k-length' dataset.
'rope_theta' was set to '1000000.0'. Trained with Axolotl. | [] | [
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] |
null | transformers |
# Model Card for Japanese DeBERTa V3 base
## Model description
This is a Japanese DeBERTa V3 base model pre-trained on LLM-jp corpus v1.0.
## How to use
You can use this model for masked language modeling as follows:
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.... | {"language": ["en", "ja"], "license": "apache-2.0", "library_name": "transformers", "tags": ["deberta", "deberta-v3"], "datasets": ["wikipedia", "EleutherAI/pile", "bigcode/the-stack", "mc4"], "metrics": ["accuracy"], "programming_language": ["C", "C++", "C#", "Go", "Java", "JavaScript", "Lua", "PHP", "Python", "Ruby",... | ku-nlp/deberta-v3-base-japanese | null | [
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"dataset:mc4",
"license:apache-2.0",
"endpoints_compatible",
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] | null | 2024-04-23T05:08:20+00:00 | [] | [
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| Model Card for Japanese DeBERTa V3 base
=======================================
Model description
-----------------
This is a Japanese DeBERTa V3 base model pre-trained on LLM-jp corpus v1.0.
How to use
----------
You can use this model for masked language modeling as follows:
You can also fine-tune this mode... | [] | [
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] |
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