Dayhoff-170M-UR90-HL-26000

microsoft/Dayhoff-170M-UR90-HL-26000

Publisher微软（Microsoft）Verified

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Dayhoff 是一个蛋白质序列数据和生成式语言模型的集合体，旨在为蛋白质语言建模研究提供广泛支持。该模型可用于无条件设计蛋白质序列、零样本预测突变对适应度的影响、在序列空间中为结构基序设计支架，以及通过同源物条件生成指定家族的新型蛋白质。该模型能够原生预测零样本突变对适应度的影响，通过进化或结构背景条件对结构基序进行支架设计，并在指定家族内执行引导式生成。模型采用混合状态空间Mamba层与Transformer自注意力机制，交织混合专家模块以最大化容量同时保持效率。模型原

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Model details

模型介绍

中文整理

# Dayhoff 模型卡片

Model use case

Dayhoff 是一个蛋白质序列数据和生成式语言模型的集合体，旨在为蛋白质语言建模研究提供广泛支持。该模型可用于无条件设计蛋白质序列、零样本预测突变对适应度的影响、在序列空间中为结构基序设计支架，以及通过同源物条件生成指定家族的新型蛋白质。

## 主要能力

该模型能够原生预测零样本突变对适应度的影响，通过进化或结构背景条件对结构基序进行支架设计，并在指定家族内执行引导式生成。模型采用混合状态空间Mamba层与Transformer自注意力机制，交织混合专家模块以最大化容量同时保持效率。模型原生支持长上下文处理，可同时处理单个序列和展开的多序列比对。采用N→C和C→N双向自回归目标进行训练，支持顺序无关的填充任务，并可扩展至数十亿参数规模。

## 输入输出

*输入：** 单个蛋白质序列、多序列比对（MSA）、或同源物信息

*输出：** 生成的蛋白质序列、突变效应预测、支架设计结果

运行要求

*软件环境：**
PyTorch 2.7.1
CUDA 12.8及以上
mamba-ssm
causal-conv1d
flash-attn

*硬件要求：**
1.7亿参数模型：8块NVIDIA A100或8块NVIDIA H100 GPU
30亿参数模型：176块NVIDIA H100 GPU

基本用法

推荐使用uv创建清洁环境并安装PyTorch 2.7.1，随后安装mamba-ssm、flash-attn、causal-conv1d及其依赖项。可通过HuggingFace接口访问模型和数据集。

限制

该模型仅应用于生成蛋白质序列或同源蛋白质序列集合，不得用于自然语言处理或其他生物序列（如DNA序列）的生成。不保证所有生成的序列都具有真实性。难以生成与任何天然序列无同源性的高质量序列。

License

MIT许可证

优先采用原作者提供的中文模型卡片；仅有英文说明时由闲社AI翻译整理。重要参数、许可证和商用范围请以原文为准。

你将获得什么

完整仓库方式包含该固定版本中的权重、配置、分词器及说明文件；指定版本方式只下载所选文件或整组分片。多模态模型的投影文件、配置等依赖，请按作者说明配齐。

完整仓库可能包含多个权重格式，因此需要的磁盘空间可能大于单一格式的模型大小。下载文件不等于完成模型部署。

使用前须知

运行环境

运行模型需要的设备、工具与依赖，以原作者说明为准。

授权范围

是否允许商用、修改和分发，请查看模型许可证。

闲社提供资料与镜像下载方法，不代表已运行模型或完成安全审计。下载的代码应先检查，再执行。

Problem with the information or download?

Pinned version · Multiple download options

Dayhoff-170M-UR90-HL-26000 model download

Download the full repository or choose a version or file.

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Use the Hugging Face download tool to obtain microsoft/Dayhoff-170M-UR90-HL-26000. Download Safetensors, GGUF, ONNX, configuration and other repository files. Downloading does not mean the tool can run this model.

Pinned-version file information is being completed. Existing downloads remain available, or load the file manifest below.

Choose a mirror or official source, your operating system and download scope below, then copy the command. Install the download tool first if needed.

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Choose your operating system

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Open a terminal window

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If Python is not installed, get it from the official Python website. In the terminal, enter python --version; continue when a version number appears.

First time? Install the download tool

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python -m pip install --upgrade huggingface_hub

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Run the download command

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Copying does not start a download. Paste and run the command on your device.

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Open the folder you chose. Look for the models folder. When progress stops and the terminal returns to its prompt without errors, check that all files are present. 'Copied' does not mean 'downloaded'.

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python not found: Install Python and reopen the terminal. On Windows, follow the installer's instructions to enable command-line access.

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Network interrupted: Stay in the same folder and run the same command again. The tool checks existing files.

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View the full download command

$env:HF_ENDPOINT = "https://huggingface.co"
$env:HF_HUB_DISABLE_IMPLICIT_TOKEN = "1"
$env:HF_HUB_DISABLE_XET = "1"
hf download "microsoft/Dayhoff-170M-UR90-HL-26000" --revision "35a699709fe2049a1ae4a4e39bcddd0543dc2113" --local-dir "./models/microsoft--Dayhoff-170M-UR90-HL-26000"

Files transfer directly from the source you choose, not through Xianshe servers.

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Public models do not require submitting keys to Xianshe. Restricted models still require the author's authorization. On Linux / macOS, use python3 instead of python when appropriate.