facebookresearch / MemoryMosaicsLinks
Memory Mosaics are networks of associative memories working in concert to achieve a prediction task.
☆48Updated 7 months ago
Alternatives and similar repositories for MemoryMosaics
Users that are interested in MemoryMosaics are comparing it to the libraries listed below
Sorting:
- Code for NeurIPS 2024 Spotlight: "Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations"☆82Updated 10 months ago
- ☆34Updated 7 months ago
- ☆53Updated last year
- ☆85Updated last year
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆38Updated 2 months ago
- ☆102Updated 11 months ago
- ☆98Updated last year
- ☆72Updated last year
- Code for reproducing our paper "Not All Language Model Features Are Linear"☆77Updated 9 months ago
- ☆28Updated 6 months ago
- The repository contains code for Adaptive Data Optimization☆25Updated 8 months ago
- 📄Small Batch Size Training for Language Models☆43Updated last week
- Language models scale reliably with over-training and on downstream tasks☆98Updated last year
- A MAD laboratory to improve AI architecture designs 🧪☆127Updated 8 months ago
- [NeurIPS 2024] Goldfish Loss: Mitigating Memorization in Generative LLMs☆90Updated 9 months ago
- nanoGPT-like codebase for LLM training☆102Updated 3 months ago
- Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Fl…☆75Updated last year
- LLM-Merging: Building LLMs Efficiently through Merging☆203Updated 11 months ago
- Learning from preferences is a common paradigm for fine-tuning language models. Yet, many algorithmic design decisions come into play. Ou…☆30Updated last year
- One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation☆41Updated 10 months ago
- Sparse and discrete interpretability tool for neural networks☆63Updated last year
- Official Pytorch Implementation of "The Curse of Depth in Large Language Models" by Wenfang Sun, Xinyuan Song, Pengxiang Li, Lu Yin,Yefen…☆55Updated last month
- Token Omission Via Attention☆128Updated 10 months ago
- Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters☆129Updated 8 months ago
- Simple and efficient pytorch-native transformer training and inference (batched)☆78Updated last year
- ☆34Updated 6 months ago
- ☆55Updated last year
- ☆69Updated last year
- A repository for research on medium sized language models.☆78Updated last year
- Minimal (400 LOC) implementation Maximum (multi-node, FSDP) GPT training☆131Updated last year