feat: add prepare_model_for_kbit_training and update LoRA r=64 alpha=128
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@@ -9,8 +9,8 @@ tokenizer_type: LlamaTokenizer
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# No need for BitsAndBytes configuration
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# No need for BitsAndBytes configuration
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# LoRA Configuration
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# LoRA Configuration
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lora_r: 16
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lora_r: 64
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lora_alpha: 32
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lora_alpha: 128
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lora_dropout: 0.05
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lora_dropout: 0.05
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target_modules:
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target_modules:
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- q_proj
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- q_proj
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@@ -52,6 +52,11 @@ def train(config_path):
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)
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)
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print("Model loaded with QLoRA (4-bit).")
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print("Model loaded with QLoRA (4-bit).")
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# Prepare model for k-bit training
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from peft import prepare_model_for_kbit_training
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model = prepare_model_for_kbit_training(model)
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print("Model prepared for k-bit training.")
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# Add LoRA
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# Add LoRA
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lora_config = LoraConfig(
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lora_config = LoraConfig(
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r=config["lora_r"],
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r=config["lora_r"],
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