GitHub - EleutherAI/sae-auto-interp
GitHub - KillianLucas/open-interpreter: OpenAI's Code Interpreter in your terminal, running locally
KillianLucasgithub.comMargaretC added
GitHub - a16z-infra/companion-app: AI companions with memory: a lightweight stack to create and host your own AI companions
github.comsari added
a16z just released an open source companion AI repo on gitgub. great resource for those thinking about building context-aware AI agents.
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.... See more
In just a few lines of codes, you can t
Testing framework for LLM Part
Nicolay Gerold added
VectorDB-recipes
Dive into building GenAI applications! This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects.
Dive into building GenAI applications! This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects.
- These are built using LanceDB, a free, open-source, serverless vectorDB that requires no setup .
- It integrates into python data ecosystem so you can simply start using these
lancedb • GitHub - lancedb/vectordb-recipes: High quality resources & applications for LLMs, multi-modal models and VectorDBs
Nicolay Gerold added
Goodfire | Interpretability for deploying safe and reliable generative AI models
goodfire.aicrtep added
Gemma Scope Tutorial
This is a barebones tutorial on how to use Gemma Scope, Google DeepMind's suite of Sparse Autoencoders (SAEs) on every layer and sublayer of Gemma 2 2B and 9B. Sparse Autoencoders are an interpretability tool that act like a "microscope" on language model activations. They let us zoom in on dense, compressed activations, and ex... See more
This is a barebones tutorial on how to use Gemma Scope, Google DeepMind's suite of Sparse Autoencoders (SAEs) on every layer and sublayer of Gemma 2 2B and 9B. Sparse Autoencoders are an interpretability tool that act like a "microscope" on language model activations. They let us zoom in on dense, compressed activations, and ex... See more
Google Colab
Nicolay Gerold added
GitHub Models - GitHub Docs
docs.github.com📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Tra... See more