Claude skills and agent skills

Hugging FaceSkill

huggingface-community-evals

huggingface/skills/skills/huggingface-community-evals/SKILL.md

Run 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.

Hugging FaceSkill

huggingface-datasets

huggingface/skills/skills/huggingface-datasets/SKILL.md

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.

Hugging FaceSkill

huggingface-gradio

huggingface/skills/skills/huggingface-gradio/SKILL.md

Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.

Hugging FaceSkill

huggingface-llm-trainer

huggingface/skills/skills/huggingface-llm-trainer/SKILL.md

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

Hugging FaceSkill

huggingface-local-models

huggingface/skills/skills/huggingface-local-models/SKILL.md

Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.

Hugging FaceSkill

huggingface-lora-space-builder

huggingface/skills/skills/huggingface-lora-space-builder/SKILL.md

Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.

Hugging FaceSkill

huggingface-paper-publisher

huggingface/skills/skills/huggingface-paper-publisher/SKILL.md

Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

Hugging FaceSkill

huggingface-papers

huggingface/skills/skills/huggingface-papers/SKILL.md

Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

Hugging FaceSkill

huggingface-spaces

huggingface/skills/skills/huggingface-spaces/SKILL.md

Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.

Hugging FaceSkill

huggingface-tool-builder

huggingface/skills/skills/huggingface-tool-builder/SKILL.md

Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.

Hugging FaceSkill

huggingface-trackio

huggingface/skills/skills/huggingface-trackio/SKILL.md

Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.

Hugging FaceSkill

huggingface-vision-trainer

huggingface/skills/skills/huggingface-vision-trainer/SKILL.md

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

Hugging FaceSkill

huggingface-zerogpu

huggingface/skills/skills/huggingface-zerogpu/SKILL.md

AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.

Hugging FaceSkill

transformers-js

huggingface/skills/skills/transformers-js/SKILL.md

Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.

Hugging FaceSkill

trl-training

huggingface/skills/skills/trl-training/SKILL.md

Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.

Hugging FaceSkill

sync-models

huggingface/chat-ui/.claude/skills/sync-models/SKILL.md

Sync chat-ui's model config with the HuggingFace router — add descriptions for new models, flag reasoning-capable ones, enable artifacts for models with 32B+ parameters, and prune deprecated models the router no longer serves. Use when models are released or removed on the router and prod.yaml/dev.yaml need syncing. Triggers on requests like "add new model descriptions", "update models from router", "sync models", "remove deprecated models", "prune models no longer on the router", or when explicitly invoking /sync-models.

Hugging FaceSkill

hf-release-notes

huggingface/huggingface_hub/.opencode/skills/hf-release-notes/SKILL.md

Generate Hugging Face Hub (huggingface_hub) release notes from cached PR JSON files. Use when asked to draft release notes from PR files.

Hugging FaceSkill

upload-post-image

huggingface/blog/.agents/skills/upload-post-image/SKILL.md

Use when adding or migrating non-thumbnail images for a Hugging Face Blog post. Uploads body images to the Hugging Face documentation-images dataset, updates the Markdown, and verifies the new links.

Hugging FacePipes a download into a shellSkill

hf-cli

huggingface/OpenEnv/.agents/skills/hf-cli/SKILL.md

Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing repositories, models, datasets, and Spaces on the Hugging Face Hub. Replaces now deprecated `huggingface-cli` command.

Often used withhuggingface-local-models

Hugging FaceSkill

openenv-cli

huggingface/OpenEnv/.agents/skills/openenv-cli/SKILL.md

OpenEnv CLI (`openenv`) for scaffolding, validating, building, and pushing OpenEnv environments.