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Duplicate from localmodels/LLM

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+ ---
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+ duplicated_from: localmodels/LLM
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+ ---
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+ # Vicuna 33B v1.3 GPTQ
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+
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+ From LMSYS: https://huggingface.co/lmsys/vicuna-33b-v1.3
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+
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+ ---
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+
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+ | Model | Bits | Group Size | Act Order (desc_act) | File Size | ExLlama Compatible? | Made With | Description |
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+ | ------ | ---- | ---------- | -------------------- | --------- | ------------------- | --------- | ----------- |
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+ | vicuna-33b-GPTQ-4bit--1g.act.order | 4 | None | True | 16.94 GB | True | GPTQ-for-LLaMa | Most compatible. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. |
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+
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+ ---
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+
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+ # Vicuna Model Card
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+
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+ ## Model Details
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+
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+ Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
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+
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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:** Non-commercial license
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+ - **Finetuned from model:** [LLaMA](https://arxiv.org/abs/2302.13971).
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+
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+ ### Model Sources
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+
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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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+
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+ ## Uses
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+
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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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+
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+ ## How to Get Started with the Model
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+
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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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+
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+ ## Training Details
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+
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+ Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning.
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+ The training data is around 140K 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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+
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+ ## Evaluation
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+
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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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+
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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)
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