Notes on AI experiments

(perhaps rename to AI practice and experience (as a nod to an early software journal))

LLM in a browser (Simon Willison): "I don’t need a language model that can answer any question I have about the world from its baked in training data. I ~~need~~ want something that can manipulate language in useful ways. I care about summarization, and fact extraction, and answering questions about larger text." https://simonwillison.net/2023/Apr/16/web-llm/
What’s in the RedPajama-Data-1T LLM training set: https://simonwillison.net/2023/Apr/17/redpajama-data/
good documentation on using SimpleVectorIndex with a service_context and with inserting more content into the index: LlamaIndex Usage Pattern - LlamaIndex (gpt-index.readthedocs.io)
question answering over documents: https://python.langchain.com/en/latest/use_cases/question_answering.html
and from reddit r/LocalLLaMA (the "prompt engineering" caution seems interesting) https://www.reddit.com/r/LocalLLaMA/comments/133vfk3/i_recently_tested_the_mpt_1b_redpajama_dolly/
https://www.reddit.com/r/LocalLLaMA/comments/12x1g24/how_to_install_vicuna_language_model_on_mac_2_ways/
https://agi-sphere.com/vicuna-mac/
using HuggingFace, OpenAI, Cohere models with langchain: https://medium.com/the-techlife/using-huggingface-openai-and-cohere-models-with-langchain-db57af14ac5b
- this would be a better resource if the code was proof-read before posting. sigh
HuggingFace Transformers documentation:
https://huggingface.co/docs/transformers/task_summary