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- repo: https://github.com/astral-sh/ruff-pre-commit
Copyright 2020 The HuggingFace Team. All rights reserved.
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**Organization developing the model**
<img src="assets/logo.png" alt="Stanford-Alpaca" style="width: 50%; min-width: 300px; display: block; margin: auto;">
To enable more open-source research on instruction following large language models, we use generate 52K instruction-followng demonstrations using OpenAI's text-davinci-003 model.
- repo: https://github.com/pre-commit/pre-commit-hooks
[](https://github.com/hiyouga/LLaMA-Factory/stargazers)
[](https://github.com/hiyouga/LLaMA-Factory/stargazers)
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Qwen-7B uses BPE tokenization on UTF-8 bytes using the `tiktoken` package.
<a href="README_CN.md">中文</a>  |  <a href="README.md">English</a>  |  日本語 |  <a href="README_FR.md">Français</a> |  <a href="README_ES.md">Español</a>
> 注:作为术语的“tokenization”在中文中尚无共识的概念对应,本文档采用英文表达以利说明。
Qwen-7B は `tiktoken` パッケージを使用して、UTF-8 バイトを BPE トークン化します。
Large language models have recently attracted an extremely large amount of
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<a href="README_CN.md">中文</a>  |  <a href="README.md">English</a>  |  <a href="README_JA.md">日本語</a>  |  Français |  <a href="README_ES.md">Español</a>
flash attention是一个用于加速模型训练推理的可选项,且仅适用于Turing、Ampere、Ada、Hopper架构的Nvidia GPU显卡(如H100、A100、RTX 3090、T4、RTX 2080),您可以在不安装flash attention的情况下正常使用模型进行推理。