Model Fine-Tuning Pipeline
Adapting model weights using parameter-efficient fine-tuning (PEFT).
Workflow Sequence
01
Action Node 1
Collect instruction-response dataset in JSON format
02
Action Node 2
Quantize base models using bitsandbytes (4-bit)
03
Action Node 3
Train LoRA adapters using Hugging Face Transformers
04
Action Node 4
Merge weights and export to GGUF format for local serving.