EleutherAI / features-across-timeLinks
Understanding how features learned by neural networks evolve throughout training
☆39Updated last year
Alternatives and similar repositories for features-across-time
Users that are interested in features-across-time are comparing it to the libraries listed below
Sorting:
- ☆69Updated last year
- Sparse and discrete interpretability tool for neural networks☆64Updated last year
- Minimum Description Length probing for neural network representations☆20Updated 9 months ago
- Experiments for efforts to train a new and improved t5☆75Updated last year
- Google Research☆46Updated 3 years ago
- Codes and files for the paper Are Emergent Abilities in Large Language Models just In-Context Learning☆33Updated 10 months ago
- ☆52Updated last year
- Code for PHATGOOSE introduced in "Learning to Route Among Specialized Experts for Zero-Shot Generalization"☆91Updated last year
- Engineering the state of RNN language models (Mamba, RWKV, etc.)☆32Updated last year
- Gemstones: A Model Suite for Multi-Faceted Scaling Laws (NeurIPS 2025)☆29Updated last month
- Official implementation of "BERTs are Generative In-Context Learners"☆32Updated 8 months ago
- Aioli: A unified optimization framework for language model data mixing☆28Updated 9 months ago
- Implementation of Influence Function approximations for differently sized ML models, using PyTorch☆15Updated 2 years ago
- Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment☆60Updated last year
- Synthetic data generation and benchmark implementation for "Episodic Memories Generation and Evaluation Benchmark for Large Language Mode…☆56Updated last month
- This repository includes code to reproduce the tables in "Loss Landscapes are All You Need: Neural Network Generalization Can Be Explaine…☆40Updated 2 years ago
- ☆55Updated 2 years ago
- ☆36Updated 3 years ago
- PyTorch library for Active Fine-Tuning☆93Updated last month
- Code Release for "Broken Neural Scaling Laws" (BNSL) paper☆59Updated 2 years ago
- Embedding Recycling for Language models☆38Updated 2 years ago
- ☆111Updated 9 months ago
- Codebase for Context-aware Meta-learned Loss Scaling (CaMeLS). https://arxiv.org/abs/2305.15076.☆25Updated last year
- Evaluation of neuro-symbolic engines☆39Updated last year
- ☆81Updated last year
- Universal Neurons in GPT2 Language Models☆31Updated last year
- ☆36Updated 2 years ago
- ☆68Updated last year
- Few-shot Learning with Auxiliary Data☆31Updated last year
- Reference implementation for Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model☆43Updated last month