Alpaca (Fine-tuned LLaMA)
Also worth considering Instruct-tuned LLaMA models that can run on consumer hardware, such as 
https://github.com/tloen/alpaca-lora.  A basic LangChainJS package for Alpaca is here https://github.com/linonetwo/langchain-alpaca
It would be great to see LangChain integrate with Standford's Alpaca 7B model, a fine-tuned LlaMa (see https://github.com/hwchase17/langchain/issues/1473).

Standford created an AI able to generate outputs that were largely on par with OpenAI’s `text-davinci-003` and regularly better than GPT-3 — all for a fraction of the computing power and price.

Stanford's Alpaca is a language model that was fine-tuned from Meta's LLaMA with 52,000 instructions generated by GPT-3.5[[1]](https://the-decoder.com/stanfords-alpaca-shows-that-openai-may-have-a-problem/). The researchers used AI-generated instructions to train Alpaca 7B, which exhibits many GPT-3.5-like behaviors[[1]](https://the-decoder.com/stanfords-alpaca-shows-that-openai-may-have-a-problem/). In a blind test using input from the Self-Instruct Evaluation Set, both models performed comparably[[1]](https://the-decoder.com/stanfords-alpaca-shows-that-openai-may-have-a-problem/)[[2]](https://github.com/tatsu-lab/stanford_alpaca). However, Alpaca has problems common to other language models such as hallucinations, toxicity, and stereotyping[[1]](https://the-decoder.com/stanfords-alpaca-shows-that-openai-may-have-a-problem/). The team is releasing an interactive demo, the training dataset, and the training code for research purposes[[1]](https://the-decoder.com/stanfords-alpaca-shows-that-openai-may-have-a-problem/)[[4]](https://crfm.stanford.edu/2023/03/13/alpaca.html).

Alpaca is still under development and has limitations that need to be addressed. The researchers have not yet fine-tuned the model to be safe and harmless[[2]](https://github.com/tatsu-lab/stanford_alpaca). They encourage users to be cautious when interacting with Alpaca and report any concerning behavior to help improve it[[2]](https://github.com/tatsu-lab/stanford_alpaca).

LLaMA is a new open-source language model from Meta Research that performs as well as closed-source models. Stanford's Alpaca is a fine-tuned version of LLaMA that can respond to instructions like ChatGPT[[3]](https://replicate.com/blog/replicate-alpaca). It functions more like a fancy version of autocomplete than a conversational bot[[3]](https://replicate.com/blog/replicate-alpaca).

The researchers are releasing their findings about an instruction-following language model dubbed Alpaca. They trained the Alpaca model on 52K instruction-following demonstrations generated in the style of self-instruct using `text-davinci-003`. On the self-instruct evaluation set, Alpaca shows many behaviors similar to OpenAI’s `text-davinci-003` but is also surprisingly small and easy/cheap to reproduce[[4]](https://crfm.stanford.edu/2023/03/13/alpaca.html).