Welcome to llm-tracker.info. This is a personal site I started to keep my notes focused around Large Language Models and Generative AI.
- If you are looking for a pure list of open LLMs, check out Extractum’s LLM Explorer (it’s sortable/filterable! Here’s a view of the current top of the (heavily gamed) HuggingFace LLM Leaderboard for example - for better leaderboards, see List of Evals)
- Eugene Yan and others maintain a list of Open LLMs (restricted to commercial use licensed models).
- I also keep an LLM Worksheet that includes a less-maintained list of Foundational models, but includes a bunch of raw inferencing benchmarks and other information hidden in there…
While I’ve been steadily adding/updating a lot of these docs, they are mostly working notes and are not particularly well organized. There’s also other similar notebooks/guides. Check out:
- https://genai-handbook.github.io/ - a 2024-06 notebook aiming to give a good GenAI technical overview (aimed at those with a strong technical background)
- https://github.com/mlabonne/llm-course - Maxime Labonne’s practical guide for fine-tuning, testing LLMs and the like
- https://fleuret.org/francois/lbdl.html - “This book is a short introduction to deep learning for readers with a STEM background, originally designed to be read on a phone screen.”
- https://github.com/stas00/ml-engineering - “This is an open collection of methodologies, tools and step by step instructions to help with successful training of large language models and multi-modal models.”
In 2024 a lot more of my time has gone into training Japanese AI models and in a co-founding a Japanese AI startup, Shisa.AI.
- https://huggingface.co/augmxnt/shisa-7b-v1 - original release of leading-edge open Japanese LLM
- https://github.com/AUGMXNT/shisa/wiki/ - a lot of related docs
- https://huggingface.co/shisa-ai and https://github.com/shisa-ai/ are where the new work is ongoing
- I’ve also started publishing some articles on my HF page: https://huggingface.co/leonardlin
Popular Content
Eventually I plan to make a custom Quartz component for recently updated, new, and popular content, but for now a few places to start:
- Getting Started - a good starting point if you’re new to the world of LLMs
- StyleTTS 2 Setup Guide - this seems to show it in searches
- AMD GPUs - an up-to-date guide on getting ROCm set up for inferencing and updated performance tests
- Qwen Fine Tune - a guide on Qwen fine-tuning, trying out a number of training scripts.