Aleph-Alpha-Research / scalingLinks
Scaling is a distributed training library and installable dependency designed to scale up neural networks, with a dedicated module for training large language models.
☆64Updated 3 weeks ago
Alternatives and similar repositories for scaling
Users that are interested in scaling are comparing it to the libraries listed below
Sorting:
- an open source reproduction of NVIDIA's nGPT (Normalized Transformer with Representation Learning on the Hypersphere)☆107Updated 7 months ago
- Experiments for efforts to train a new and improved t5☆75Updated last year
- ☆142Updated last month
- The simplest, fastest repository for training/finetuning medium-sized GPTs.☆168Updated 4 months ago
- ☆81Updated last year
- ☆46Updated last year
- Train a SmolLM-style llm on fineweb-edu in JAX/Flax with an assortment of optimizers.☆18Updated 3 months ago
- Minimal (400 LOC) implementation Maximum (multi-node, FSDP) GPT training☆132Updated last year
- OpenCoconut implements a latent reasoning paradigm where we generate thoughts before decoding.☆172Updated 9 months ago
- ☆102Updated 9 months ago
- Large scale 4D parallelism pre-training for 🤗 transformers in Mixture of Experts *(still work in progress)*☆87Updated last year
- A set of Python scripts that makes your experience on TPU better☆54Updated last month
- EvaByte: Efficient Byte-level Language Models at Scale☆110Updated 6 months ago
- Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters☆130Updated 10 months ago
- nanoGPT-like codebase for LLM training