xrsrke / pipegooseLinks
Large scale 4D parallelism pre-training for ๐ค transformers in Mixture of Experts *(still work in progress)*
โ86Updated 2 years ago
Alternatives and similar repositories for pipegoose
Users that are interested in pipegoose are comparing it to the libraries listed below
Sorting:
- some common Huggingface transformers in maximal update parametrization (ยตP)โ87Updated 3 years ago
- JAX implementation of the Llama 2 modelโ215Updated last year
- A set of Python scripts that makes your experience on TPU betterโ54Updated 3 months ago
- โ92Updated last year
- โ20Updated 2 years ago
- Implementation of the Llama architecture with RLHF + Q-learningโ170Updated 11 months ago
- Inference code for LLaMA models in JAXโ120Updated last year
- โ63Updated 3 years ago
- Minimal (400 LOC) implementation Maximum (multi-node, FSDP) GPT trainingโ132Updated last year
- โ167Updated 2 years ago
- โ47Updated last year
- Train very large language models in Jax.โ210Updated 2 years ago
- The simplest, fastest repository for training/finetuning medium-sized GPTs.โ181Updated 6 months ago
- Experiments with generating opensource language model assistantsโ97Updated 2 years ago
- NeurIPS Large Language Model Efficiency Challenge: 1 LLM + 1GPU + 1Dayโ259Updated 2 years ago
- Exploring finetuning public checkpoints on filter 8K sequences on Pileโ116Updated 2 years ago
- OSLO: Open Source for Large-scale Optimizationโ175Updated 2 years ago
- Implementation of the specific Transformer architecture from PaLM - Scaling Language Modeling with Pathways - in Jax (Equinox framework)โ189Updated 3 years ago
- A puzzle to learn about promptingโ135Updated 2 years ago
- Understand and test language model architectures on synthetic tasks.โ248Updated 3 months ago
- โ52Updated last year
- โ124Updated last year
- โ94Updated 2 years ago
- Code repository for the c-BTM paperโ108Updated 2 years ago
- seqax = sequence modeling + JAXโ169Updated 5 months ago
- โ53Updated last year
- Code for the paper "The Impact of Positional Encoding on Length Generalization in Transformers", NeurIPS 2023โ137Updated last year
- Experiments for efforts to train a new and improved t5โ76Updated last year
- MoE training for Me and You and maybe other peopleโ315Updated last week
- A flexible and efficient implementation of Flash Attention 2.0 for JAX, supporting multiple backends (GPU/TPU/CPU) and platforms (Triton/โฆโ33Updated 10 months ago