README.md

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iHuggingfaceHub😜: Your own private huggingface hub server!

Goal

Make your own huggingface hub with local files.

You can access local model and dataset by using huggingface transformers and datasets lib, just like:

import os
os.environ['HF_ENDPOINT'] = 'http://server-ip:9999'
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval()

Deploy

Local Mode

pip3 install -r requirements.txt
python3 app.py

Docker Mode

docker compose up -d

Usage

step1. put models in 'files' directory

mkdir -p files/Qwen
cd files/Qwen
git clone https://huggingface.co/Qwen/Qwen-7B-Chat

step2. use transformers lib to load model

import os

def main():
    os.environ['HF_ENDPOINT'] = 'http://127.0.0.1:9999'  # change to app.py host ip
    from transformers import AutoModelForCausalLM, AutoTokenizer
    from transformers.generation import GenerationConfig
    tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True)
    model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval()
    generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True,
                                                         resume_download=True)
    model.generation_config = generation_config
    response, history = model.chat(tokenizer, "你好", history=None)
    print(response)


if __name__ == '__main__':
    main()

TODO

• Add revision support
• Add dataset support