File size: 2,389 Bytes
213c699 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | import os
import sys
import subprocess
from pathlib import Path
def run_notebook():
print("============================================================")
print(" QuantHive — Notebook-based GRPO Training (HF Jobs)")
print("============================================================")
# 1. Install necessary execution dependencies
print("📦 Installing notebook execution tools...")
subprocess.run([sys.executable, "-m", "pip", "install", "-q", "nbconvert", "nbformat", "ipykernel", "huggingface_hub"], check=True)
# 2. Execute the notebook
print("🚀 Executing mate_training.ipynb (mimicking Colab flow)...")
try:
# We run it with --to notebook --execute --inplace
subprocess.run([
"jupyter", "nbconvert",
"--to", "notebook",
"--execute",
"--inplace",
"mate_training.ipynb"
], check=True)
print("✅ Notebook execution successful!")
except subprocess.CalledProcessError as e:
print(f"❌ Notebook execution failed: {e}")
# We don't exit here because the notebook might have saved partial results
# 3. Model Storage to HF Hub
# The notebook saves to ./quanthive-trader-grpo-lora
model_path = Path("quanthive-trader-grpo-lora")
if model_path.exists():
print(f"📡 Found trained model at {model_path}. Pusing to HF Hub...")
try:
from huggingface_hub import HfApi
api = HfApi()
repo_id = "ARKAISW/quanthive-trader-grpo-lora"
# Use HF_TOKEN if available in environment
token = os.environ.get("HF_TOKEN")
api.upload_folder(
folder_path=str(model_path),
repo_id=repo_id,
repo_type="model",
token=token
)
print(f"✅ Model successfully pushed to https://huggingface.co/{repo_id}")
except Exception as e:
print(f"⚠️ Model push failed: {e}")
print("You can manually push the 'quanthive-trader-grpo-lora' folder later.")
else:
print("❌ Trained model folder not found. Check notebook output for errors.")
print("============================================================")
print("🏁 Processing Finished.")
if __name__ == "__main__":
run_notebook()
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