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This toolbox already includes 18 Jupyter notebooks specially optimized for Qwen2.5. The logs of successful runs are also provided. More notebooks will be regularly added.
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To run the code in the toolbox, CUDA 12.4 and PyTorch 2.4 are recommended. PyTorch 2.5 might already work but I didn't test it yet.
Toolbox content
Supervised Fine-Tuning with Chat Templates (5 notebooks)
Full fine-tuning
LoRA fine-tuning
QLoRA fine-tuning with Bitsandbytes quantization
QLoRA fine-tuning with AutoRound quantization
LoRA and QLoRA fine-tuning with Unsloth
Multi-GPU QLoRA/LoRA fine-tuning with FSDP
Preference Optimization (3 notebooks)
Full DPO training (TRL and Transformers)
DPO training with LoRA (TRL and Transformers)
ORPO training with LoRA (TRL and Transformers)
Multi-GPU QLoRA/LoRA DPO Training with FSDP
Quantization (3 notebooks)
AWQ
AutoRound (with code to quantize Qwen 2.5 72B)
GGUF for llama.cpp
Inference with Qwen2.5 Instruct and Your Own Fine-tuned Qwen2.5 (4 notebooks)
Transformers with and without a LoRA adapter
vLLM offline and online inference
Ollama (not released yet)
llama.cpp
Merging (3 notebooks)
Merge a LoRA adapter into the base model
Merge a QLoRA adapter into the base model
Merge several Qwen2.5 models into one with mergekit (not released yet)