Embeddings

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

Nomic Atlas Python Client

Explore, label, search and share massive datasets in your web browser.

This repository contains Python bindings for working with Nomic Atlas, the world’s most powerful unstructured data interaction platform. Atlas supports datasets from hundreds to tens of millions of points, and supports data modalities ranging from text ... See more

What is feder

Feder is a JavaScript tool designed to aid in the comprehension of embedding vectors. It visualizes index files from Faiss, HNSWlib, and other ANN libraries to provide insight into how these libraries function and the concept of high-dimensional vector embeddings. Currently, Feder is primarily focused on the IVF_FLAT index file type f... See more

Introduction

This library provides utilities for generating and scoring text explanations of sparse autoencoder (SAE) features. The explainer and scorer models can be run locally or acessed using API calls via OpenRouter.

Note that we're still actively cleaning up the codebase and scripts.

Installation

Install this library as a local editable install... See more