h2ogpt
llama.cpp
h2ogpt | llama.cpp | |
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28 | 773 | |
10,458 | 56,891 | |
2.4% | - | |
10.0 | 10.0 | |
2 days ago | 6 days ago | |
Python | C++ | |
Apache License 2.0 | MIT License |
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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
llama.cpp
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
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Embeddings are a good starting point for the AI curious app developer
Have just done this recently for local chat with pdf feature in https://recurse.chat. (It's a macOS app that has built-in llama.cpp server and local vector database)
Running an embedding server locally is pretty straightforward:
- Get llama.cpp release binary: https://github.com/ggerganov/llama.cpp/releases
- Mixtral 8x22B
- Llama.cpp: Improve CPU prompt eval speed
What are some alternatives?
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
privateGPT - Interact with your documents using the power of GPT, 100% privately, no data leaks [Moved to: https://github.com/zylon-ai/private-gpt]
gpt4all - gpt4all: run open-source LLMs anywhere
llama_index - LlamaIndex is a data framework for your LLM applications
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
local_llama - This repo is to showcase how you can run a model locally and offline, free of OpenAI dependencies.
ggml - Tensor library for machine learning
h2o-llmstudio - H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://h2oai.github.io/h2o-llmstudio/
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM