Upload train_concise.py with huggingface_hub

train_concise.py

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+# /// script
+# dependencies = ["trl>=0.12.0", "peft>=0.7.0", "datasets", "transformers", "torch", "accelerate"]
+# ///
+
+from datasets import load_dataset
+from peft import LoraConfig
+from trl import SFTTrainer, SFTConfig
+
+# Load YOUR custom dataset
+dataset = load_dataset("passagereptile455/concise-tech-explanations", split="train")
+
+# Train on concise style
+trainer = SFTTrainer(
+    model="Qwen/Qwen2.5-0.5B",
+    train_dataset=dataset,
+    peft_config=LoraConfig(r=16, lora_alpha=32, target_modules="all-linear"),
+    args=SFTConfig(
+        output_dir="qwen-concise",
+        max_steps=50,  # Small dataset, fewer steps
+        per_device_train_batch_size=1,
+        gradient_accumulation_steps=4,
+        logging_steps=10,
+        learning_rate=2e-4,  # Higher LR for small dataset
+        push_to_hub=True,
+        hub_model_id="passagereptile455/qwen-concise-style",
+        hub_private_repo=True,
+    )
+)
+
+trainer.train()
+trainer.push_to_hub()
+print("Done! Model trained on YOUR concise style.")