This docker image is based on the Stanford 'Alpaca'[1] model, which is a fine-tuned version of Meta's 'LLaMa'[3] foundational large language model. It uses the 'dalai'[2] tool download and Access the Alpaca model via an webserver.
clone repo.
docker build -t alpaca_7b_llm .
docker container run -it -p 3000:3000 --name alpaca_7b_llm alpaca_7b_llm
npx dalai serve
Access the server on http://localhost:3000
Be aware of this term by Stanford:
We emphasize that Alpaca is intended only for academic research and any commercial use is prohibited. There are three factors in this decision: First, Alpaca is based on LLaMA, which has a non-commercial license, so we necessarily inherit this decision. Second, the instruction data is based on OpenAI’s text-davinci-003, whose terms of use prohibit developing models that compete with OpenAI. Finally, we have not designed adequate safety measures, so Alpaca is not ready to be deployed for general use.
[1] Stanford Alpaca: An Instruction-following LLaMA model (2023), Rohan Taori and Ishaan Gulrajani and Tianyi Zhang and Yann Dubois and Xuechen Li and Carlos Guestrin and Percy Liang and Tatsunori B. Hashimoto. https://crfm.stanford.edu/2023/03/13/alpaca.html
[2] Dalai: Run LLaMA and Alpaca on your computer. https://github.com/cocktailpeanut/dalai
[3] LLaMa: Meta, https://ai.facebook.com/blog/large-language-model-llama-meta-ai/, https://github.com/facebookresearch/llama