mediar-ai/packages/skills/skills/huggingface-jobs
packages/skills/skills/huggingface-jobs/SKILL.md
# Hugging Face Jobs Run any workload on fully managed Hugging Face infrastructure - data processing, batch inference, experiments, and scheduled tasks. ## Prerequisites - HF_TOKEN environment variable - Hugging Face Pro/Team/Enterprise plan ## Instructions ### Common Use Cases - Data Processing - Transform, filter, analyze large datasets - Batch Inference - Run inference on thousands of samples - Experiments & Benchmarks - Reproducible ML experiments - Model Training - Fine-tune models (se
$ install --global
skillsauthnpx skillsauth add mediar-ai/skillhubz packages/skills/skills/huggingface-jobsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
Hugging Face Jobs
Run any workload on fully managed Hugging Face infrastructure - data processing, batch inference, experiments, and scheduled tasks.
Prerequisites
- HF_TOKEN environment variable
- Hugging Face Pro/Team/Enterprise plan
Instructions
Common Use Cases
- Data Processing - Transform, filter, analyze large datasets
- Batch Inference - Run inference on thousands of samples
- Experiments & Benchmarks - Reproducible ML experiments
- Model Training - Fine-tune models (see model-trainer skill for TRL)
- Scheduled Jobs - Automate recurring tasks
UV Scripts (Recommended)
hf_jobs("uv", {
"script": """
# /// script
# dependencies = ["datasets", "transformers"]
# ///
from datasets import load_dataset
dataset = load_dataset("cais/mmlu", split="train[:100]")
print(f"Loaded {len(dataset)} examples")
""",
"flavor": "cpu-basic",
"timeout": "30m",
"secrets": {"HF_TOKEN": "$HF_TOKEN"}
})
Hardware Flavors
| Use Case | Flavor | Cost/hr | |----------|--------|---------| | Basic tasks | cpu-basic | ~$0.10 | | Light GPU | t4-small | ~$0.75 | | Medium GPU | a10g-small | ~$3.50 | | Large GPU | a10g-large | ~$5.00 | | Heavy compute | a100-large | ~$10.00 |
CLI Commands
# Submit job from URL
hf jobs uv run \
--flavor cpu-basic \
--timeout 30m \
--secrets HF_TOKEN \
"https://example.com/script.py"
# Check status
hf jobs ps
hf jobs logs <job-id>
hf jobs inspect <job-id>
hf jobs cancel <job-id>
Important Notes
- Jobs run in isolated Docker containers
- Local file paths don't work - use inline code or URLs
- Always set timeout (default 30min may be too short)
- Use
secretsparameter to pass HF_TOKEN for Hub access - Results are lost unless pushed to Hub
Notes
- For model training, see the huggingface-model-trainer skill
- Uses PEP 723 inline dependencies
- Supports CPU, GPU, and TPU hardware
Source: huggingface/skills
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