Skill UI

This SDK provides comprehensive content moderation capabilities for Python applications using Azure AI. It allows developers to analyze text and images to detect harmful content across multiple categories, including hate speech, violence, sexual content, and self-harm. Key features include multi-severity classification, managing custom blocklists, and analyzing content from local files or URLs. Ideal for pre-moderating user-generated content (UGC) or AI outputs to ensure platform safety.

This SDK provides comprehensive content moderation capabilities for Python applications using Azure AI. It allows developers to analyze text and images to detect harmful content across multiple categories, including hate speech, violence, sexual content, and self-harm. Key features include multi-severity classification, managing custom blocklists, and analyzing content from local files or URLs. Ideal for pre-moderating user-generated content (UGC) or AI outputs to ensure platform safety.

CLIP enables general-purpose vision-language tasks through zero-shot image classification, similarity scoring, semantic search, and content moderation using pretrained contrastive embeddings without fine-tuning.

Enables Claude to invoke the computer-vision-processor plugin, auto-generating Python calls to run object detection, classification, and segmentation on user-provided images for detailed analysis.

This skill provides a managed cloud environment for training and fine-tuning advanced vision models. Users can build and customize models for object detection (e.g., DETR, YOLOS), image classification, and segmentation (SAM/SAM2). By leveraging Hugging Face Jobs, training is executed on powerful cloud GPUs without requiring local GPU setup, and all resulting models are automatically saved to the Hugging Face Hub.

Transformers.js allows developers to run state-of-the-art machine learning models directly within JavaScript/TypeScript environments (browser, Node.js). It supports a comprehensive range of tasks including NLP (text generation, summarization, translation), Computer Vision (image classification, object detection), and Audio processing. This capability enables building fully client-side, multimodal AI applications without requiring a dedicated Python backend or server infrastructure.

Train object detection, image classification, and SAM/SAM2 segmentation models locally or on Hugging Face Jobs with dataset validation and Hub saving.

Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes like Node.js, Bun, and Deno, enabling text analysis, image classification, speech recognition, and multimodal AI applications without a Python backend.