Upload train_production.py with huggingface_hub

train_production.py

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+# /// script
+# dependencies = ["trl>=0.12.0", "peft>=0.7.0", "trackio", "torch", "transformers", "datasets"]
+# ///
+
+from datasets import load_dataset
+from peft import LoraConfig
+from trl import SFTTrainer, SFTConfig
+import trackio
+
+print("🚀 Starting ComfyUI Specialist Training (Production)")
+print("=" * 60)
+
+# Load our custom ComfyUI dataset
+dataset = load_dataset("lokegud/comfyui-workflows-dataset", split="train")
+print(f"📊 Dataset loaded: {len(dataset)} examples")
+
+# Split for evaluation
+dataset_split = dataset.train_test_split(test_size=0.15, seed=42)
+train_dataset = dataset_split["train"]
+eval_dataset = dataset_split["test"]
+
+print(f"📈 Train: {len(train_dataset)} | Eval: {len(eval_dataset)}")
+
+# LoRA configuration - optimized for 1.5B model
+peft_config = LoraConfig(
+    r=32,  # Higher rank for better learning
+    lora_alpha=64,
+    lora_dropout=0.05,
+    target_modules=["q_proj", "v_proj", "k_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
+    task_type="CAUSAL_LM"
+)
+
+# Training configuration
+training_args = SFTConfig(
+    output_dir="comfyui-specialist-v1",
+    num_train_epochs=3,
+    per_device_train_batch_size=2,
+    per_device_eval_batch_size=2,
+    gradient_accumulation_steps=8,  # Effective batch size: 16
+    learning_rate=2e-4,
+    warmup_steps=20,
+    logging_steps=5,
+    eval_strategy="steps",
+    eval_steps=20,
+    save_strategy="steps",
+    save_steps=50,
+    save_total_limit=3,
+    load_best_model_at_end=True,
+    metric_for_best_model="eval_loss",
+    greater_is_better=False,
+    push_to_hub=True,
+    hub_model_id="lokegud/comfyui-specialist-v1",
+    hub_strategy="every_save",
+    hub_private_repo=False,
+    report_to="trackio",
+    project="comfyui-specialist",
+    run_name="production-v1",
+    gradient_checkpointing=True,
+    max_length=2048,  # Longer context for full workflows
+    dataset_text_field="messages",  # Chat format
+)
+
+print("🔧 Initializing trainer with Qwen2.5-1.5B-Instruct...")
+
+# Initialize trainer
+trainer = SFTTrainer(
+    model="Qwen/Qwen2.5-1.5B-Instruct",
+    train_dataset=train_dataset,
+    eval_dataset=eval_dataset,
+    peft_config=peft_config,
+    args=training_args,
+)
+
+print("🏋️ Training ComfyUI Specialist...")
+trainer.train()
+
+print("📤 Pushing final model to Hub...")
+trainer.push_to_hub()
+
+print("✅ Training complete!")
+print(f"📦 Model: lokegud/comfyui-specialist-v1")
+print(f"📊 Trackio: https://lokegud-trackio.hf.space/")