taufeeque9 / codebook-featuresLinks
Sparse and discrete interpretability tool for neural networks
☆64Updated last year
Alternatives and similar repositories for codebook-features
Users that are interested in codebook-features are comparing it to the libraries listed below
Sorting:
- Universal Neurons in GPT2 Language Models☆30Updated last year
- Sparse Autoencoder Training Library☆55Updated 5 months ago
- ☆23Updated 9 months ago
- ☆110Updated 8 months ago
- Code for reproducing our paper "Not All Language Model Features Are Linear"☆83Updated 11 months ago
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆59Updated 2 years ago
- ☆33Updated 9 months ago
- Notebooks accompanying Anthropic's "Toy Models of Superposition" paper☆129Updated 3 years ago
- ☆108Updated 8 months ago
- ☆27Updated 2 years ago
- Investigating the generalization behavior of LM probes trained to predict truth labels: (1) from one annotator to another, and (2) from e…☆28Updated last year
- Understanding how features learned by neural networks evolve throughout training☆39Updated last year
- PyTorch library for Active Fine-Tuning☆93Updated last month
- Code for the ICLR 2024 paper "How to catch an AI liar: Lie detection in black-box LLMs by asking unrelated questions"☆71Updated last year
- ☆92Updated last year
- A mechanistic approach for understanding and detecting factual errors of large language models.☆46Updated last year
- Gemstones: A Model Suite for Multi-Faceted Scaling Laws (NeurIPS 2025)☆29Updated last month
- ☆36Updated 2 years ago
- Yet another random morning idea to be quickly tried and architecture shared if it works; to allow the transformer to pause for any amount…☆52Updated 2 years ago
- [NeurIPS 2024] Goldfish Loss: Mitigating Memorization in Generative LLMs☆92Updated 11 months ago
- Official implementation of FIND (NeurIPS '23) Function Interpretation Benchmark and Automated Interpretability Agents☆51Updated last year
- A library for efficient patching and automatic circuit discovery.☆78Updated 3 months ago
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆84Updated last year
- ☆36Updated 3 years ago
- Language models scale reliably with over-training and on downstream tasks☆100Updated last year
- Official repository for our paper, Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Mode…☆19Updated 11 months ago
- Open source replication of Anthropic's Crosscoders for Model Diffing☆59Updated last year
- ☆86Updated last year
- Minimum Description Length probing for neural network representations☆20Updated 9 months ago
- ☆30Updated 2 years ago