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Training & Fine-tuning

Distributed-training libraries, parameter-efficient fine-tuning methods and post-training toolkits for adapting foundation models to new tasks and preferences.

Unslothunsloth.aiFine-tuning toolkit that speeds up LoRA and full training while cutting GPU memory use, with free notebooks.Training & Fine-tuningOpen source★ 77.2kDeepSpeeddeepspeed.aiLibrary for large-scale distributed training and inference, known for the ZeRO memory-optimisation family.Training & Fine-tuningOpen source★ 43.2kPEFThuggingface.coParameter-efficient fine-tuning methods such as LoRA, letting large models adapt on modest hardware.Training & Fine-tuningOpen source★ 21.8kTRLhuggingface.coHugging Face library for post-training models with supervised fine-tuning, DPO, GRPO and other preference-optimisation methods.Training & Fine-tuningOpen source★ 19.4kMegatron-LMgithub.comNVIDIA's research codebase for training transformer models at scale with tensor, pipeline and sequence parallelism.Training & Fine-tuningOpen source★ 18.1knanoGPTgithub.comAndrej Karpathy's minimal repository for training and fine-tuning medium-sized GPTs, a classic learning resource.Training & Fine-tuningOpen source★ 63.6kAxolotlaxolotl.aiConfig-driven tool for fine-tuning open models across many architectures and training methods.Training & Fine-tuningOpen source★ 12.5kWeights & Biaseswandb.aiExperiment tracking, model registry and dashboards used by many research teams to compare training runs; now part of CoreWeave.Training & Fine-tuningFreemium★ 11.3ktorchtunegithub.comPyTorch-native library of hackable recipes for fine-tuning and experimenting with LLMs.Training & Fine-tuningOpen source★ 5.8k

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