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--- |
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license: openrail |
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language: |
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- en |
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pipeline_tag: text-generation |
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library_name: transformers |
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--- |
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## Original model card |
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Buy me a coffee if you like this project ;) |
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<a href="https://www.buymeacoffee.com/s3nh"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a> |
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#### Description |
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GGML Format model files for [This project](https://huggingface.co/lmsys/vicuna-13b-v1.5). |
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### inference |
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```python |
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import ctransformers |
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from ctransformers import AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained(output_dir, ggml_file, |
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gpu_layers=32, model_type="llama") |
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manual_input: str = "Tell me about your last dream, please." |
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llm(manual_input, |
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max_new_tokens=256, |
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temperature=0.9, |
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top_p= 0.7) |
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``` |
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# Original model card |
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## Model Details |
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Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT. |
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- **Developed by:** [LMSYS](https://lmsys.org/) |
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- **Model type:** An auto-regressive language model based on the transformer architecture |
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- **License:** Llama 2 Community License Agreement |
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- **Finetuned from model:** [Llama 2](https://arxiv.org/abs/2307.09288) |
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### Model Sources |
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- **Repository:** https://github.com/lm-sys/FastChat |
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- **Blog:** https://lmsys.org/blog/2023-03-30-vicuna/ |
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- **Paper:** https://arxiv.org/abs/2306.05685 |
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- **Demo:** https://chat.lmsys.org/ |
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## Uses |
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The primary use of Vicuna is research on large language models and chatbots. |
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The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. |
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## How to Get Started with the Model |
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- Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights |
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- APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api |
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## Training Details |
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Vicuna v1.5 is fine-tuned from Llama 2 with supervised instruction fine-tuning. |
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The training data is around 125K conversations collected from ShareGPT.com. |
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See more details in the "Training Details of Vicuna Models" section in the appendix of this [paper](https://arxiv.org/pdf/2306.05685.pdf). |
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## Evaluation |
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Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this [paper](https://arxiv.org/pdf/2306.05685.pdf) and [leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard). |
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## Difference between different versions of Vicuna |
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See [vicuna_weights_version.md](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md) |
