instructor-embedding
h2ogpt
| instructor-embedding | h2ogpt | |
|---|---|---|
| 4 | 28 | |
| 1,703 | 10,458 | |
| 3.1% | 3.0% | |
| 5.9 | 10.0 | |
| 10 days ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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instructor-embedding
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My experience on starting with fine tuning LLMs with custom data
If you li embeddings and vector DB, you should look into this: https://github.com/HKUNLP/instructor-embedding
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Build Personal ChatGPT Using Your Data
If you look at a embeddings leaderboard [1], one of the top competitors called InstructorXL [2] is just a pip install away. It's neck and neck with Ada v2 except for a shorter input length and half the dimensions, with the added benefit that you'll always have the model available.
Most of the other options just work with the transformers library.
[1] https://huggingface.co/spaces/mteb/leaderboard
[2] https://github.com/HKUNLP/instructor-embedding
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I've made a customisable SMS personal assistant which has infinite and persistent semantic memory.
Use instructor-embedding to to make it 100% local and even maybe quick relationship lookup (embed relationship info with sentiment analysis instruction)
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Whisper Transcription Formatting
First.I believe having srt subtitles as whisper result would be better.Essentially you don't need just a list of words like YouTube does.You need something more structured.I don't remember what whisper outputs so I might be wrong.There is whisperx for that as example. And then maybe use gpt index over it.Or something like instructor model That can work.
h2ogpt
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
As others have said you want RAG.
The most feature complete implementation I've seen is h2ogpt[0] (not affiliated).
The code is kind of a mess (most of the logic is in an ~8000 line python file) but it supports ingestion of everything from YouTube videos to docx, pdf, etc - either offline or from the web interface. It uses langchain and a ton of additional open source libraries under the hood. It can run directly on Linux, via docker, or with one-click installers for Mac and Windows.
It has various model hosting implementations built in - transformers, exllama, llama.cpp as well as support for model serving frameworks like vLLM, HF TGI, etc or just OpenAI.
You can also define your preferred embedding model along with various other parameters but I've found the out of box defaults to be pretty sane and usable.
[0] - https://github.com/h2oai/h2ogpt
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chatgpt alternative
Here's the links: https://github.com/h2oai/h2ogpt/blob https://github.com/h2oai/h2ogpt/blob/main/docs/README_LangChain.md
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Went down the rabbit hole of 100% local RAG, it works but are there better options?
Take a look at h2ogpt. It's open and local with API (incoming and outgoing) and impressive feature set, including RAG from docs, images, and web search.
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[SEEKING ADVICE] Looking for Existing Repos (Open-Source, VM-Hosted, & GPU-Compatible)
I've stumbled upon h2ogptas a potential starting point. Are there better solutions or repositories that can meet these requirements?
- H2Oai GPT CPU
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Open source Q&A chatbot UI Recommendation?
Any recommendations for an open source repos that support web based chat ui where you can upload docs,pds,links,etc? So far i found https://github.com/openchatai/OpenChat but it doesnt support llama, claude, etc. Theres also https://github.com/h2oai/h2ogpt but their gradio UI is overly complicated (meant for technical people) and not user friendly.
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My experience on starting with fine tuning LLMs with custom data
I'm also working on the finetuning of models for Q&A and I've finetuned llama-7b, falcon-40b, and oasst-pythia-12b using HuggingFace's SFT, H2OGPT's finetuning script and lit-gpt.
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H2O.ai Introduces h2oGPT: A Suite of Open-Source Code Repositories for Democratizing Large Language Models (LLMs)
Github link: https://github.com/h2oai/h2ogpt
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tokenizers error is driving me nuts
quite a number of AI tools written in Python do not work for me and usually because of the same error: RuntimeError: Failed to import transformers.models.auto because of the following error (look up to see its traceback): No module named 'tokenizers.tokenizers' This time it's https://github.com/h2oai/h2ogpt
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LLM for PDFs
privateGPT or h2ogpt
What are some alternatives?
openai-cookbook - Examples and guides for using the OpenAI API
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
Nuggt - An Autonomous LLM Agent that runs on Wizcoder-15B
privateGPT - Interact with your documents using the power of GPT, 100% privately, no data leaks [Moved to: https://github.com/zylon-ai/private-gpt]
vlite - fast vector database made in numpy
llama_index - LlamaIndex is a data framework for your LLM applications
easydiffusion - Easiest 1-click way to create beautiful artwork on your PC using AI, with no tech knowledge. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image.
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
lit-gpt - Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. [Moved to: https://github.com/Lightning-AI/litgpt]
local_llama - This repo is to showcase how you can run a model locally and offline, free of OpenAI dependencies.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
h2o-llmstudio - H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/