ProfessorGPTProfessorGPT
Hugging Face
Hugging FaceHugging Face· v1.0.0
analysisOfficial
Official Provider SkillView repo

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

Files1 files
SKILL.md108 lines
Loading editor…

Install

Recommended

One command — your agent picks it up automatically.

Select an AI agent above to see the install command.

or

Manual Install

More steps

Download the file and paste it into your agent's system prompt.

Skill details

Versionv1.0.0
AuthorHugging Face
Categoryanalysis
Skill IDhuggingface/skills/skills/huggingface-datasets

Related skills

Hf CliHugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configHf McpUse Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.Hf MemHugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face HubHuggingface BestUse when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skiHuggingface Community EvalsRun evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.Huggingface GradioBuild Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.