Fine-tuning & Training

Produces the weights that layer 1 serves.

• UnslothlibraryHand-written kernels that cut LoRA memory and time sharply.unsloth.aiMore about Unsloth in this index
• AxolotllibraryConfiguration-driven fine-tuning across common architectures.axolotl.aiMore about Axolotl in this index
• LLaMA-FactoryplatformUnified interface for SFT, DPO and RLHF on open models.github.comMore about LLaMA-Factory in this index
• PEFTlibraryParameter-efficient fine-tuning methods such as LoRA and QLoRA.github.comMore about PEFT in this index
• TRLlibraryHugging Face library of post-training trainers for SFT, DPO and GRPO.github.comMore about TRL in this index
• DeepSpeedlibraryZeRO sharding and pipeline parallelism for large-scale training.deepspeed.aiMore about DeepSpeed in this index
• Megatron-LMlibraryTensor and pipeline parallel training for multi-GPU clusters.github.comMore about Megatron-LM in this index
• torchtunelibraryPyTorch-native recipes for fine-tuning and aligning open models.github.comMore about torchtune in this index
• Hugging Face TRLplatformPreference and reward optimisation on top of any PEFT setup.huggingface.coMore about Hugging Face TRL in this index
• ColabplatformHosted GPUs for small runs and quick experiments.colab.research.google.comMore about Colab in this index
• ReplicateplatformHosted fine-tuning and deployment for open models.replicate.comMore about Replicate in this index
• Weights & Biases LaunchplatformManaged training runs with sweeps and artifact tracking.wandb.aiMore about Weights & Biases Launch in this index