instructor-embedding
lit-gpt
instructor-embedding | lit-gpt | |
---|---|---|
4 | 4 | |
1,703 | 5,243 | |
3.1% | - | |
5.9 | 9.6 | |
10 days ago | about 2 months 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.
lit-gpt
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LLMs on your local Computer (Part 1)
git clone --depth=1 https://github.com/Lightning-AI/lit-gpt cd lit-gpt pip install -r requirements.txt pip install bitsandbytes==0.41.0 huggingface_hub python scripts/download.py --repo_id stabilityai/stablelm-zephyr-3b --from_safetensors=True python scripts/convert_hf_checkpoint.py --checkpoint_dir checkpoints/stabilityai/stablelm-zephyr-3b --dtype float32
- LoRA from Scratch implementation for LLM finetuning
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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.
- finetune Falcon 40B in 30 minutes using LLaMA adapter
What are some alternatives?
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
openai-cookbook - Examples and guides for using the OpenAI API
Nuggt - An Autonomous LLM Agent that runs on Wizcoder-15B
axolotl - Go ahead and axolotl questions
vlite - fast vector database made in numpy
semantra - Multi-tool for semantic search
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.
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.
PdfGptIndexer - RAG based tool for indexing and searching PDF text data using OpenAI API and FAISS (Facebook AI Similarity Search) index, designed for rapid information retrieval and superior search accuracy.