cyberneticlibrary

Run cloud training on Hugging Face

hugging-face-jobsskillsetup L30
Sheshiyer/skill-clusters
What it does

Submit Python workloads to managed Hugging Face cloud GPUs/TPUs

Best for

When running data processing, batch inference, model training, or ML experiments without local GPU setup or infrastructure complexity.

Inputs
  • · Python script
  • · dependencies (via uv)
  • · secrets (HF_TOKEN)
  • · optional timeout, env vars
Outputs
  • · job ID
  • · monitoring URL
  • · job logs
  • · results persisted to Hub
Requires
  • · Hugging Face Jobs MCP
  • · HF_TOKEN for Hub auth
  • · uv (package manager)
Preconditions

HF pro/team/enterprise plan, HF_TOKEN with write permission, script provided as string

Failure modes
  • · Timeout exceeded before job completes losing all progress
  • · HF_TOKEN not passed as secret causing auth failure
  • · script writes to local files instead of pushing to Hub
Trust signals
  • · Jobs run asynchronously on cloud
  • · $HF_TOKEN placeholder auto-replaced by MCP
  • · Trackio monitoring included