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pythonaiweb scrapermcppdfgitdockertypescript
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ai
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machine-learning
10.1K

huggingface-llm-trainer

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.

huggingface
huggingface
data-ai
open
machine-learning
10.1K

huggingface-vision-trainer

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.

huggingface
huggingface
data-ai
open
machine-learning
10.1K

transformers-js

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.

huggingface
huggingface
data-ai
open
knowledge-base
10.1K

huggingface-paper-publisher

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.

huggingface
huggingface
documentation
open
academic
10.1K

huggingface-papers

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.

huggingface
huggingface
research
open
lab-tools
10.1K

huggingface-trackio

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
huggingface
research
open
system-admin
10.1K

hf-cli

Hugging 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; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.

huggingface
huggingface
tools
open
data-engineering
10.1K

electric-new-feature

End-to-end guide for adding a new synced feature with Electric and TanStack DB. Covers the full journey: design Postgres schema, set REPLICA IDENTITY FULL, define shape, create proxy route, set up TanStack DB collection with electricCollectionOptions, implement optimistic mutations with txid handshake (pg_current_xact_id, awaitTxId), and build live queries with useLiveQuery. Also covers migration from old ElectricSQL (electrify/db pattern does not exist), current API patterns (table as query param not path, handle not shape_id). Load when building a new feature from scratch.

electric-sql
electric-sql
data-ai
open
sql-databases
10.1K

electric-schema-shapes

Design Postgres schema and Electric shape definitions together for a new feature. Covers single-table shape constraint, cross-table joins using multiple shapes, WHERE clause design for tenant isolation, column selection for bandwidth optimization, replica mode choice (default vs full for old_value), enum casting in WHERE clauses, and txid handshake setup with pg_current_xact_id() for optimistic writes. Load when designing database tables for use with Electric shapes.

electric-sql
electric-sql
databases
open
debugging
10.1K

debug

Troubleshooting all sorts of failures, crashes, exceptions and errors using debug capabilities. Analyze accuracy, performance, or memory issues. Dump tensors and intermediate blobs. Serialize IRs, execution graphs. Enable verbose, logging. Profile execution. Compare layer outputs. Inspect, trace or dump transformations. Identify executed operations, nodes, primitives, kernels.

openvinotoolkit
openvinotoolkit
tools
open
backend
10K

scaffold-connector

Build a new OpenMetadata connector from scratch — scaffold JSON Schema, Python boilerplate, and AI context using schema-first architecture with code generation across Python, Java, TypeScript, and auto-rendered UI forms.

open-metadata
open-metadata
development
open
productivity-tools
10K

playwright-test

Generate robust, zero-flakiness Playwright E2E tests following OpenMetadata patterns. Creates comprehensive test files with proper waits, API validation, multi-role permissions, and complete entity lifecycle management.

open-metadata
open-metadata
tools
open
git-workflows
10K

planning

Use when starting a non-trivial feature, refactor, or multi-file change. Forces structured design thinking before writing any code - brainstorm approaches, get approval, then create a step-by-step implementation plan.

open-metadata
open-metadata
devops
open
code-quality
10K

verification

Use before claiming any task is complete. Requires running actual verification commands and showing evidence — no "should work" claims without proof.

open-metadata
open-metadata
testing-security
open
debugging
10K

connector-audit

Deep reliability audit for OpenMetadata connectors — runs 7 investigation prompts (metadata, errors, auth, lineage, scale, synthesis, implementation) against connector standards

open-metadata
open-metadata
tools
open
debugging
10K

connector-review

Review an OpenMetadata connector against golden standards. Runs multi-agent analysis covering architecture, code quality, type safety, testing, and performance. When a PR number is given, automatically posts the quality summary to the PR description and a detailed review as a PR comment.

open-metadata
open-metadata
tools
open
debugging
10K

systematic-debugging

Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.

open-metadata
open-metadata
tools
open
git-workflows
10K

create-pr

Creates a GitHub Pull Request for RunCat365 following the project's PR template. Use this skill whenever the user wants to open, submit, or create a PR, pull request, or wants to propose changes to the main branch.

Kyome22
Kyome22
devops
open
sales-marketing
10K

design-style-skill

Select a consistent visual design system for PPT slides using radius/spacing style recipes. Use when users ask for overall style direction or component styling consistency. Includes Sharp/Soft/Rounded/Pill recipes, component mappings, typography/spacing rules, and mixing guidance. Triggers: 风格, style, radius, spacing, 圆角, 间距, PPT风格, 视觉风格, design style, component style.

MiniMax-AI
MiniMax-AI
business
open
sales-marketing
10K

minimax-music-playlist

Generate personalized music playlists by analyzing the user's music taste from local apps (Apple Music, QQ Music) and generation feedback history. Triggers on "generate playlist", "make a playlist", "歌单", "推荐歌单", "根据我的口味生成", "personalized playlist", "music taste", "音乐画像", "scan my music", "扫描我的音乐", "playlist based on my taste", "根据喜好生成".

MiniMax-AI
MiniMax-AI
business
open
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