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We as members, contributors, and leaders pledge to make participation in our
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- repo: https://github.com/astral-sh/ruff-pre-commit
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Copyright 2020 The HuggingFace Team. All rights reserved.
**Organization developing the model**
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.
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<img src="assets/logo.png" alt="Stanford-Alpaca" style="width: 50%; min-width: 300px; display: block; margin: auto;">
[](https://github.com/hiyouga/LLaMA-Factory/stargazers)
- repo: https://github.com/pre-commit/pre-commit-hooks
[](https://github.com/hiyouga/LLaMA-Factory/stargazers)
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<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>
Large language models have recently attracted an extremely large amount of
Qwen-7B uses BPE tokenization on UTF-8 bytes using the `tiktoken` package.
> 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。
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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> |  <a href="README_FR.md">Français</a> |  Español
<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 is an option for accelerating training and inference. Only NVIDIA GPUs of Turing, Ampere, Ada, and Hopper architecture, e.g., H100, A100, RTX 3090, T4, RTX 2080, can support flash attention. **You can use our models without installing it.**