DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
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Making large AI models cheaper, faster and more accessible
- deep-learning
- hpc
- large-scale
- data-parallelism
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Ongoing research training transformer models at scale
- large-language-models
- model-para
- transformers
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
Python package built to ease deep learning on graph, on top of existing DL frameworks.
- deep-learning
- graph-neural-networks
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
- nlp
- embedding
- bert
- ernie
PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.
- model
Go ahead and axolotl questions
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
An open-source framework for machine learning and other computations on decentralized data.
A production-grade, high-efficiency Agentic RL framework for frontier LLMs with validated recipes.