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funsloth-hfjobs
Training manager for Hugging Face Jobs - launch fine-tuning on HF cloud GPUs with optional WandB monitoring
$ 安裝
git clone https://github.com/chrisvoncsefalvay/funsloth /tmp/funsloth && cp -r /tmp/funsloth/skills/funsloth-hfjobs ~/.claude/skills/funsloth// tip: Run this command in your terminal to install the skill
SKILL.md
name: funsloth-hfjobs description: Training manager for Hugging Face Jobs - launch fine-tuning on HF cloud GPUs with optional WandB monitoring
Hugging Face Jobs Training Manager
Run Unsloth training on Hugging Face Jobs (cloud GPU training).
Prerequisites
- HF Authentication:
huggingface-cli whoami(login if needed) - HF Jobs Access: Requires PRO subscription or org compute access
- Training notebook/script: From
funsloth-train
Workflow
1. Select Hardware
| GPU | VRAM | Cost | Best For |
|---|---|---|---|
| A10G | 24GB | ~$1.50/hr | 7-14B LoRA |
| A100 40GB | 40GB | ~$4/hr | 14-34B |
| A100 80GB | 80GB | ~$6/hr | 70B |
| H100 | 80GB | ~$8/hr | Fastest |
See references/HARDWARE_GUIDE.md for model-to-GPU mapping.
2. Convert Notebook to Script
HF Jobs requires PEP 723 script format:
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git",
# "torch>=2.0",
# "transformers>=4.45",
# "trl>=0.12",
# "peft>=0.13",
# "datasets>=2.18",
# ]
# ///
Use scripts/train_sft.py as a template.
3. Optional: WandB Integration
Add to script:
import wandb
wandb.init(project="funsloth-training")
# Add report_to="wandb" in TrainingArguments
Set: export WANDB_API_KEY="your-key"
4. Estimate Costs
Use the cost estimator:
python scripts/estimate_cost.py --tokens {total_tokens} --platform hfjobs
5. Launch Job
# Create job config
cat > job_config.yaml << 'EOF'
compute:
gpu: {gpu_type}
gpu_count: 1
script: train_hfjobs.py
outputs:
- /outputs/*
EOF
# Submit
huggingface-cli jobs create --config job_config.yaml
6. Monitor Progress
huggingface-cli jobs status {job_id}
huggingface-cli jobs logs {job_id} --follow
WandB: https://wandb.ai/{username}/funsloth-training
7. Download Artifacts
from huggingface_hub import snapshot_download
snapshot_download(repo_id="{username}/funsloth-job", local_dir="./outputs")
8. Handoff
Offer funsloth-upload for Hub upload with model card.
Error Handling
| Error | Resolution |
|---|---|
| No HF Jobs access | Get PRO subscription |
| OOM | Reduce batch size or upgrade GPU |
| Job timeout | Enable checkpointing |
| Script error | Check PEP 723 dependencies |
Bundled Resources
- scripts/train_sft.py - PEP 723 script template
- scripts/estimate_cost.py - Cost estimation
- references/PLATFORM_COMPARISON.md - HF Jobs vs alternatives
- references/HARDWARE_GUIDE.md - VRAM requirements
- references/TROUBLESHOOTING.md - Common issues
Repository

chrisvoncsefalvay
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chrisvoncsefalvay/funsloth/skills/funsloth-hfjobs
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Updated4d ago
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