starcoder VS private-gpt

Use local LLM like: https://github.com/bigcode-project/starcoder

Here's the script I use to merge a LoRA onto a base model: https://gist.github.com/TheBloke/d31d289d3198c24e0ca68aaf37a19032 (a slightly modified version of https://github.com/bigcode-project/starcoder/blob/main/finetune/merge_peft_adapters.py)

consult: https://github.com/bigcode-project/starcoder/issues/6 https://huggingface.co/bigcode/starcoder/discussions/12

StarCoder - The biggest open source code LLM. It’s a free VS code extension. Looks great for coding, makes you wonder how long things like Github Copilot and Ghostwriter can afford to charge when we have open source building things like this. Link to github [Link] Link to HF [Link]

Outside of just using GPT4, which works well, this is supposedly the solution, though I haven't tried it just yet. starcoder/README.md at main · bigcode-project/starcoder · GitHub

GitHub link: https://github.com/bigcode-project/starcoder/tree/main

PrivateGPT is a nice tool for this. It's not exactly what you're asking for, but it gets part of the way there.

https://github.com/zylon-ai/private-gpt

Further details available at: https://docs.privategpt.dev/api-reference/api-reference/ingestion

Run https://github.com/imartinez/privateGPT

Then

make ingest /path/to/folder/with/files

Then chat to the LLM.

Done.

Docs: https://docs.privategpt.dev/overview/welcome/quickstart

PrivateGPT repository in case anyone's interested: https://github.com/imartinez/privateGPT . It doesn't seem to be linked from their official website.

I’m preparing a small internal tool for my work to search documents and provide answers (with references), I’m thinking of using GPT4All [0], Danswer [1] and/or privateGPT [2].

The RAG technique is very close to what I have in mind, but I don’t want the LLM to “hallucinate” and generate answers on its own by synthesizing the source documents. As stated by many others, we’re living in interesting times.

[0] https://gpt4all.io/index.html

[1] https://www.danswer.ai/

[2] https://github.com/imartinez/privateGPT

https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_a...

https://github.com/imartinez/privateGPT

I've been playing around with https://github.com/imartinez/privateGPT and https://github.com/simonw/llm and wanted to create a simple Python package that made it easier to run ChatGPT-like LLMs on your own machine, use them with non-public data, and integrate them into practical applications.

This resulted in Python package I call OnPrem.LLM.

In the documentation, there are examples for how to use it for information extraction, text generation, retrieval-augmented generation (i.e., chatting with documents on your computer), and text-to-code generation: https://amaiya.github.io/onprem/

Enjoy!