Execute Python workloads on Hugging Face Jobs with GPU/CPU resources.
npx skills add https://github.com/tayyabexe/skills --skill hugging-face-jobs-tayyabexe
Please help me install this Agent Skill. Skill: hugging-face-jobs Source: https://github.com/tayyabexe/skills/tree/main/skills/hugging-face-jobs Command: npx skills add https://github.com/tayyabexe/skills --skill hugging-face-jobs-tayyabexe
This Skill allows users to run any Python workload, including data processing, model inference, and training, on managed Hugging Face cloud infrastructure without local setup.
Use the hugging-face-jobs skill to run a Python script named 'train_model.py' on a 'a10g-large' GPU with a 2-hour timeout.
High-intent search queries and answers about installing and using this skill.
You can run Python workloads on Hugging Face cloud infrastructure by submitting UV scripts or Docker containers directly to managed CPUs or GPUs. This approach eliminates local setup by handling resource allocation, authentication via HF_TOKEN secrets, and monitoring.
Yes, you can train a large language model on a GPU cluster using Hugging Face Jobs. The service supports scalable cloud-based computation for ML tasks, allowing you to configure specific hardware flavors like 'a10g-large' GPUs and set custom timeouts for training workloads.
The best way to persist results from batch inference jobs is to use the built-in result persistence feature of Hugging Face Jobs. It allows your executed Python workloads and data pipelines to save their outputs directly to the Hugging Face Hub automatically.
Yes, Hugging Face Jobs supports Docker containers for script execution. You can submit your Python workloads directly as UV scripts or package them within Docker images to manage dependencies and environments on cloud compute resources.
You configure hardware flavors and timeouts for data processing pipelines by specifying parameters during job submission on Hugging Face. This resource management allows you to allocate appropriate CPUs or GPUs and define execution limits for your compute tasks.
Himanshu040604Submit and manage computational workloads on Hugging Face Jobs infrastructure.
huggingfaceManage Hugging Face Hub resources via the hf CLI.
cpich3gExecute Python scripts or Docker containers on Hugging Face Jobs infrastructure.
davpatel605-beepDeploy and execute machine learning workloads on serverless GPU infrastructure.
