Skill collection · huggingface
skills agent skills by huggingface
24 skills from huggingface/skills are listed in the directory, across 5 categories. 12 skills have a full page with install steps and a pre-install summary.
View huggingface/skills on GitHub
At a glance
| Publisher | Hugging Face Official |
|---|---|
| Repository | github.com/huggingface/skills |
| Listed skills | 24 |
| Security scan | Not scanned |
| Categories | AI Agents and LLM Engineering, DevOps and Cloud, Data, Analytics and Databases, Developer Tools and Frameworks, Science and Research |
| License | Apache-2.0 |
| Last commit | October 8, 2026 |
| Install every skill | npx skills add https://github.com/huggingface/skills |
| README badge | Get the badge for this listing |
Show the listing in your README
This general badge links to the repository listing. For the two quality badges and feature offer, choose Get badges beside a skill below. Each skill keeps its own score and grade.
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<a href="https://skills.suedeai.ai/directory/huggingface/skills/"><img src="https://skills.suedeai.ai/directory/huggingface/skills/badge.svg" alt="Suede Skills Directory: listed" height="20"></a>Limited-time feature offer: display either the numeric or letter badge in your repository or skill README (both also qualify), then request badge verification. Eligible skills scoring 80–99 can receive a featured placement after Suede verifies at least one valid badge linked to the skill’s listing. Suede has not announced an end date.
Skills in huggingface/skills
Linked names open the skill's directory page; the rest open the skill folder on GitHub. Descriptions on rows without a page are quoted from each SKILL.md.
| Skill | Category | What it does |
|---|---|---|
| hf-cloud-python-env-setup 85/100 · B | DevOps | Sets up an isolated Python environment with the right Python version and current boto3 for SageMaker and other AWS automation work. |
| hf-cloud-sagemaker-iam-preflight 83/100 · B | DevOps | Ensures a usable SageMaker execution role exists before deploying or training, checking for existing roles first rather than blindly creating IAM roles. |
| hf-cloud-sagemaker-production-defaults 80/100 · B | DevOps | Creates SageMaker endpoints (real-time, scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default, using provided deploy scripts. |
| hf-cloud-serving-image-selection 84/100 · B | DevOps | Picks the right serving container for a SageMaker model deployment and finds its current image URI, preferring HuggingFace Deep Learning Containers. |
| huggingface-community-evals 86/100 · B | AI agents | Runs evaluations for Hugging Face Hub models on local hardware using inspect-ai and lighteval, including backend selection and choosing between vLLM, Transformers, and accelerate. |
| huggingface-local-models 80/100 · B | AI agents | Selects models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm, covering quant selection, conversion, and OpenAI-compatible serving. |
| huggingface-lora-space-builder 75/100 · C | AI agents | Builds and publishes a Gradio demo on Hugging Face Spaces for a user-provided LoRA, including the base pipeline and a task-specific UI. |
| huggingface-spaces 83/100 · B | DevOps | Builds, deploys, and maintains applications on Hugging Face Spaces, including Gradio, Docker, and Static SDKs, ZeroGPU, debugging build failures, and inference providers. |
| huggingface-tool-builder 83/100 · B | Dev tools | Builds reusable scripts that fetch, enrich, or process data from the Hugging Face API, especially when chaining API calls or automating repeated tasks. |
| huggingface-trackio 83/100 · B | AI agents | Tracks and visualizes ML training experiments with Trackio, including metric logging, training alerts with webhooks, real-time dashboards, and metric retrieval through the CLI. |
| huggingface-zerogpu 85/100 · B | AI agents | Guides writing and reviewing Gradio code for Hugging Face ZeroGPU Spaces, covering @spaces.GPU usage, requirements configuration, and ZeroGPU-specific constraints like pickle isolation. |
| train-sentence-transformers 83/100 · B | AI agents | Trains and fine-tunes sentence-transformers models, including bi-encoders, cross-encoders, sparse encoders, and multi-vector encoders, with guidance on loss selection, hard-negative mining, evaluators, and Hub publishing. |
| hf-cli 76/100 · C | AI agents | Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging… |
| hf-cloud-aws-context-discovery 83/100 · B | DevOps | Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any…Get badges  Choose the numeric badge, the letter badge, or both. Each links to this skill’s Suede listing; either valid linked badge can qualify for the feature offer. Markdown HTML |
| hf-cloud-sagemaker-deployment-planner 79/100 · C | DevOps | Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a… |
| hf-mcp 72/100 · C | AI agents | Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use… |
| hf-mem 67/100 · D | AI agents | Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub |
| huggingface-best 81/100 · B | AI agents | Use 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…Get badges  Choose the numeric badge, the letter badge, or both. Each links to this skill’s Suede listing; either valid linked badge can qualify for the feature offer. Markdown HTML |
| huggingface-datasets 77/100 · C | Data | Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download… |
| huggingface-gradio 75/100 · C | AI agents | Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots. |
| huggingface-llm-trainer 72/100 · C | AI agents | Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure… |
| huggingface-papers 80/100 · B | Science | Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked…Get badges  Choose the numeric badge, the letter badge, or both. Each links to this skill’s Suede listing; either valid linked badge can qualify for the feature offer. Markdown HTML |
| huggingface-vision-trainer 72/100 · C | AI agents | Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3… |
| trl-training 77/100 · C | AI agents | Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging… |
Where this repository is cited
huggingface/skills appears in 2 curated lists: heilcheng/awesome-agent-skills, skillmatic-ai/awesome-agent-skills.