zhangxiaobai_shishen_full_4bit

zhanghuiATchina/zhangxiaobai_shishen_full_4bit

PublisherzhanghuiATchina

Download access requirementsModelScope source

本模型是基于InternLM-chat-7B预训练模型，通过 XiaChuFang Recipe Corpus食谱语料库进行FineTune，训练出来的微调模型。模型通过1,520,327种菜谱进行了1个epoch的微调训练，并进行4bit量化。使用gradio或者streamlit调用就行了。本地也可以直接使用命令行方式调用。

Text Processing

View all download instructions Mirror repository documentation and license ↗

Model details

模型介绍

中文整理

Clone with HTTP

介绍

本模型是基于InternLM-chat-7B预训练模型，通过 XiaChuFang Recipe Corpus食谱语料库进行FineTune，训练出来的微调模型。

模型通过1,520,327种菜谱进行了1个epoch的微调训练，并进行4bit量化。

模型描述

本模型是用于实现咨询菜谱的对话。

期望模型使用方式以及适用范围

使用gradio或者streamlit调用就行了。本地也可以直接使用命令行方式调用。

安?

创建conda环境

安装依赖

如何使用

编辑download.py：

执行 python download.py。

切换到下载好的模型权重目录 zhangxiaobai shishen full 4bit （一般是 ~/.cache/modelscope/hub/zhanghuiATchina/zhangxiaobai shishen full 4bit）

编辑pipeline.py

执行 python pipeline.py。

训练数据介绍

XiaChuFang Recipe Corpus

● 发布方**：清华大学,百度,北京通用人工智能研究院

● 发布时间**：2020

● 简介**：完整的食谱语料库包含1,520,327种中国食谱。其中，1,242,206食谱属于30,060菜肴。一道菜平均有41.3个食谱。食谱的平均长度是224个字符。最大长度为62,722个字符，最小长度为10个字符。食谱由415,272位作者贡献。其中，最有生产力的作者上传5,394食谱。我们提供脱敏的作者信息。

● 下载地址**： https://opendatalab.org.cn/XiaChuFang Recipe Corpus

● 论文地址**： https://arxiv.org//pdf/2210.114

模型训练流程

后续补?

数据评估及结果

后续补?

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

zhangxiaobai_shishen_full_4bit model download

Download the full repository or choose a version or file.

Download tools · More than GGUF

Use the Hugging Face download tool to obtain zhanghuiATchina/zhangxiaobai_shishen_full_4bit. 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.

Pinned version: 84f4a65dbdde11c7e0f3f2d539be18154dae6256. Downloads files only; does not start the model.

Choose a download source

Pinned ModelScope version: 84f4a65dbdde11c7e0f3f2d539be18154dae6256. Version identifiers can differ across sites. The alternative source was provided after checking weights and runtime configuration; this is not proof of a successful model run.

A checked, pinned ModelScope source is available for this model. Use the ModelScope download tool.

Choose what to download

Need just one GGUF precision? Load the file manifest and choose a version. Direct file links do not require Python; the command below can download multiple shards together.

Quantization / file

This reads the pinned version's file manifest; no model weights are downloaded.

Choose your operating system

For command-line downloads, follow these steps to get the full repository or selected files. Direct file links do not need these steps.

Open a terminal window

Create and open a folder for the model. In the folder's address bar, enter powershell and press Enter.

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

Copy this command, paste it into the terminal, press Enter and wait for installation to finish.

python -m pip install --upgrade huggingface_hub

Already installed? Continue to step 3.

Run the download command

Select the button below, paste into the same terminal and press Enter. The tool downloads all files included in the current command.

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

Where are the downloaded files?

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'.

No response or an error?

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

hf not found: Confirm that step 2 succeeded, then reopen the terminal. If needed, add Python's Scripts folder to your user PATH. Do not repeatedly download scripts.

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

Permission or disk error: Choose a writable folder with enough free space. Do not disable system security protection.

View the full download command

modelscope download --model "zhanghuiATchina/zhangxiaobai_shishen_full_4bit" --revision "84f4a65dbdde11c7e0f3f2d539be18154dae6256" --local_dir "./models/zhanghuiATchina--zhangxiaobai_shishen_full_4bit--ms-84f4a65dbdde"

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

The version is pinned. Repeating the same command checks existing files. Change the source manually if it is slow or unavailable.

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.