Intelligence artificielle

huggingface

Un entraîneur de modèles de langage qui utilise TRL sur l'infrastructure Hugging Face Jobs.

huggingface

The huggingface-paper-publisher skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on Hugging Face Hub, streamlining workflow and enhancing collaboration.

huggingface

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...

huggingface

The Hugging Face Papers skill enables developers to look up and read AI research papers in markdown, and access structured metadata such as authors and linked models. This skill benefits developers and researchers by providing easy access to AI research insights.

huggingface

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.

huggingface

This skill enables developers to test Hugging Face models locally, streamlining backend selection and model comparisons. It supports inspect-ai and lighteval for efficient evaluations.

huggingface

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

huggingface

La compétence Hugging Face Datasets pour Claude Code permet l'exploration et l'extraction de données de manière efficace. Utilisez l'API de Dataset Viewer pour récupérer des métadonnées de sous-ensemble/split, paginer des lignes, rechercher du texte et appliquer des filtres.

huggingface

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.

huggingface

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 Node.js and browsers (with WebGPU/WASM) using pre-trained models from Hugging Face Hub.

huggingface

Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.

huggingface

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.