EleutherAI / training-jacobianLinks
☆23Updated 9 months ago
Alternatives and similar repositories for training-jacobian
Users that are interested in training-jacobian are comparing it to the libraries listed below
Sorting:
- Latent Diffusion Language Models☆69Updated last year
- Engineering the state of RNN language models (Mamba, RWKV, etc.)☆32Updated last year
- Fork of Flame repo for training of some new stuff in development☆17Updated last week
- Minimum Description Length probing for neural network representations☆18Updated 7 months ago
- ☆34Updated last year
- Code for the examples presented in the talk "Training a Llama in your backyard: fine-tuning very large models on consumer hardware" given…☆14Updated last year
- GoldFinch and other hybrid transformer components☆45Updated last year
- ☆19Updated 3 months ago
- LayerNorm(SmallInit(Embedding)) in a Transformer to improve convergence☆59Updated 3 years ago
- Demonstration that finetuning RoPE model on larger sequences than the pre-trained model adapts the model context limit☆63Updated 2 years ago
- Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing☆50Updated 3 years ago
- Utilities for Training Very Large Models☆58Updated 11 months ago
- My explorations into editing the knowledge and memories of an attention network☆35Updated 2 years ago
- Implementation of a holodeck, written in Pytorch☆18Updated last year
- Automatically take good care of your preemptible TPUs☆36Updated 2 years ago
- [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling☆40Updated last year
- HomebrewNLP in JAX flavour for maintable TPU-Training☆50Updated last year
- ☆21Updated 10 months ago
- RWKV model implementation☆38Updated 2 years ago
- Triton Implementation of HyperAttention Algorithm☆48Updated last year
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆38Updated 3 months ago
- ☆82Updated last year
- A scalable implementation of diffusion and flow-matching with XGBoost models, applied to calorimeter data.☆18Updated 10 months ago
- ☆49Updated last year
- Explorations into adversarial losses on top of autoregressive loss for language modeling☆37Updated 6 months ago
- Code for the paper "Function-Space Learning Rates"☆23Updated 3 months ago
- H-Net Dynamic Hierarchical Architecture☆79Updated last month
- Explorations into the proposal from the paper "Grokfast, Accelerated Grokking by Amplifying Slow Gradients"☆101Updated 8 months ago
- Understanding how features learned by neural networks evolve throughout training☆37Updated 10 months ago
- ☆31Updated 2 months ago