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[v1] support quantization (#10161)
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examples/v1/train_qlora/quantization.yaml
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43
examples/v1/train_qlora/quantization.yaml
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model: Qwen/Qwen3-0.6B
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trust_remote_code: true
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model_class: llm
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template: qwen3_nothink
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# PEFT Configuration
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peft_config:
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name: lora
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r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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target_modules: all
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# Kernel Config
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kernel_config:
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name: auto
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include_kernels: auto
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# FSDP Config
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dist_config:
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name: fsdp2
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dcp_path: null
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# Quantization Config
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quant_config:
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name: bnb # choice: auto/bnb if auto is selected, the quantization method will be automatically selected based on the model and environment.
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quantization_bit: 4 # choice: 8/4(bnb)
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### data
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train_dataset: data/v1_sft_demo.yaml
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### training
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output_dir: outputs/test_quantization
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micro_batch_size: 1
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cutoff_len: 2048
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learning_rate: 1.0e-4
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bf16: false
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max_steps: 10
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### sample
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sample_backend: hf
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max_new_tokens: 128
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