Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: transformers

英語版ディレクトリ

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

162K
Stars
87/100
信頼
カテゴリ: ml-automation監査

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

13K
Stars
87/100
信頼
カテゴリ: ml-automation監査

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

67K
Stars
84/100
信頼
カテゴリ: ml-automation監査

⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

4.0K
Stars
84/100
信頼
カテゴリ: ml-automation監査

Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch

1.9K
Stars
84/100
信頼
カテゴリ: ml-automation監査

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

34K
Stars
70/100
信頼
カテゴリ: research監査

Official implementation for "RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers" (ICML 2025) , UltraViCo (ICLR 2026) and UltraImage

808
Stars
73/100
信頼
カテゴリ: media-automation監査

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

1.4K
Stars
71/100
信頼
カテゴリ: robotics-iot監査

Generative Adversarial Transformers

1.3K
Stars
69/100
信頼
カテゴリ: media-automation監査

[ICCV 2021 Oral] PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

847
Stars
70/100
信頼
カテゴリ: robotics-iot監査

FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers

508
Stars
66/100
信頼
カテゴリ: media-automation監査

[CVPR 2022] FaceFormer: Speech-Driven 3D Facial Animation with Transformers

915
Stars
63/100
信頼
カテゴリ: robotics-iot監査