data-centric-env / submit_job.py
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"""
Submit the Data-Centric AI training job to HF infrastructure.
⚠️ RECOMMENDED: Use the Colab notebook instead — it's more reliable.
https://colab.research.google.com/github/CelestialWorthyOfHeavenAndEarth/data-centric-env/blob/main/train_colab.ipynb
HF Jobs is provided as an alternative for automated / unattended runs.
Usage (Windows):
set HF_TOKEN=hf_yourtoken
python submit_job.py
Usage (Linux/Mac):
HF_TOKEN=hf_yourtoken python submit_job.py
"""
import os, sys
from huggingface_hub import HfApi
TOKEN = os.environ.get("HF_TOKEN") or input("Enter your HF token (hf_...): ").strip()
ENV_URL = "https://aswini-kumar-data-centric-env.hf.space"
REPO_URL = "https://huggingface.co/spaces/Aswini-Kumar/data-centric-env"
# Use official Unsloth Docker image — has torch 2.4.1 + compatible torchao pre-installed
# See: https://hub.docker.com/r/unsloth/unsloth/tags
DOCKER_IMAGE = "unsloth/unsloth:latest-torch241"
api = HfApi(token=TOKEN)
print("Submitting HF training job...")
print(f" Docker image: {DOCKER_IMAGE}")
print(f" ENV_URL : {ENV_URL}")
print(f" Hardware : a10g-large")
# Clone repo + run training (torchao + unsloth are pre-installed in the image)
bash_cmd = f"""
apt-get update -qq && apt-get install -y -qq git && \\
git clone {REPO_URL} /app && cd /app && \\
pip install -q openenv-core[core]>=0.2.1 scikit-learn>=1.3.0 pandas>=2.0.0 numpy matplotlib && \\
pip install -e . && \\
python hf_job_train.py
"""
job = api.run_job(
image=DOCKER_IMAGE,
command=["bash", "-c", bash_cmd],
env={
"ENV_URL": ENV_URL,
"HF_TOKEN": TOKEN,
},
flavor="a10g-large",
)
print(f"\nJob submitted!")
print(f" Job ID : {job.id}")
print(f" Status : {job.status}")
print(f" Monitor : https://huggingface.co/jobs/Aswini-Kumar/{job.id}")
print(f"\n⚡ Alternatively, use Colab for a more reliable run:")
print(f" https://colab.research.google.com/github/CelestialWorthyOfHeavenAndEarth/data-centric-env/blob/main/train_colab.ipynb")