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Upload run_cloud_training.py with huggingface_hub

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  1. run_cloud_training.py +8 -0
run_cloud_training.py CHANGED
@@ -21,6 +21,9 @@ from transformers.data.data_collator import DataCollatorMixin
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  from peft import LoraConfig
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  from unsloth import FastLanguageModel
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  # Disable flash attention globally
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  os.environ["TRANSFORMERS_NO_FLASH_ATTENTION"] = "1"
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@@ -514,6 +517,11 @@ def train(config_path, dataset_name, output_dir):
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  dtype = torch.float16 if hardware_config.get("fp16", True) else None
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  model, tokenizer = load_model_safely(model_name, max_seq_length, dtype)
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  # Try different approaches to apply LoRA
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  logger.info("Applying LoRA to model")
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  from peft import LoraConfig
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  from unsloth import FastLanguageModel
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+ # Configure PyTorch memory allocator for better memory management
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+ os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
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+
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  # Disable flash attention globally
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  os.environ["TRANSFORMERS_NO_FLASH_ATTENTION"] = "1"
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  dtype = torch.float16 if hardware_config.get("fp16", True) else None
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  model, tokenizer = load_model_safely(model_name, max_seq_length, dtype)
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+ # Disable generation capabilities for research training
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+ logger.info("Disabling generation capabilities - Research training only")
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+ model.config.is_decoder = False
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+ model.config.task_specific_params = None
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+
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  # Try different approaches to apply LoRA
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  logger.info("Applying LoRA to model")
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