Best deep learning skills, page 9

HuggingFace Diffusers 环境配置指南，用于华为昇腾 NPU。覆盖 CANN 版本检测、PyTorch + torchnpu 安装、Diffusers 库安装及环境验证。当用户需要在昇腾 NPU 上配置 Diffusers 环境时使用。

ascend-ai-coding/awesome-ascend-skills

基于 PyTorch 框架的昇腾 NPU 模型推理融合算子优化技能。分析模型代码，识别可替换为 torchnpu 融合算子的计算模式，生成替换方案。触发场景：torchnpu 融合算子替换、MoE/Attention/FFN/Norm 等模块的推理算子适配、torchnpu API 使用咨询。基于仓库已有模型的融合算子经验，按计算语义推荐最佳方案。

ascend-ai-coding/awesome-ascend-skills

基于 PyTorch 框架的昇腾 NPU 模型推理适配与部署基线技能。从 HF 链接或本地模型代码出发，按 cann-recipes-infer 仓库规范适配到 ModelRunner 推理框架，输出可运行的标准模型目录和性能基线数据。触发场景：新模型适配到昇腾 NPU 推理框架、已有模型的部署基线采集、模型迁移和初始跑通验证。

ascend-ai-coding/awesome-ascend-skills

从用户 PyTorch/Python 代码中提取算子实现，构建为算子任务格式的标准化 任务文件。支持两种模式：单 case（单一自包含 .py，getinputs 返回单组）和 多 case（.py + 同名 .json 配对，getinputgroups 返回多组）。

ascend-ai-coding/awesome-ascend-skills

根据设计文档生成 AscendC 算子完整代码实现并完成框架适配。TRIGGER when: 设计文档已完成，需要生成 ophost/opkernel 代码、注册到 PyTorch 框架、编译测试。关键词：代码生成、ophost、opkernel、tiling、kernel、框架适配、算子注册。

ascend-ai-coding/awesome-ascend-skills

面向 Ascend PyTorch Profiler / msprof DB（如 ascendpytorchprofiler.db、msprof.db）的 SQL 分析技能。将自然语言问题（算子耗时、通信、下发、调度、schema/table 查询）转为安全可执行 SQL，并按需从官方文档提取表结构详情。

ascend-ai-coding/awesome-ascend-skills

MindSpeed-MM multimodal model suite environment setup guide for Huawei Ascend NPU.

ascend-ai-coding/awesome-ascend-skills

Directly launch Docker containers on Ascend NPU servers for users.

ascend-ai-coding/awesome-ascend-skills

A skill your agent uses when deciding whether a project is a strong ICLR submission, should be reframed for ICLR, or should be routed to NeurIPS, ICML, AAAI, AISTATS, ACL, CVPR, KDD, or another venue.

brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when training or debugging a neural net in PyTorch — the forward/loss/backward/step loop and its silent bugs, mixed precision (AMP), AdamW/LR schedules, DDP/FSDP/ZeRO…

ericrisco/rsc-harness

A skill your agent uses when predicting a column from rows of tabular features with classic models — scikit-learn pipelines, RandomForest, XGBoost/LightGBM, leak-free cross-validation, metrics for…

ericrisco/rsc-harness

Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing.

seb1n/awesome-ai-agent-skills

Triton language skill for Python GPU kernel authoring. An agent skill from mohitmishra786/low-level-dev-skills.

mohitmishra786/low-level-dev-skills

High-performance numerical computing and machine learning workflows using JAX.

majiayu000/claude-skill-registry

Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and distributed training with DeepSpeed or FSDP.

majiayu000/claude-skill-registry

PyTorch model training skill with custom training loops, gradient management, and GPU optimization.

majiayu000/claude-skill-registry

TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.

majiayu000/claude-skill-registry

Route DGL graph learning tasks across graph APIs, datasets, message passing, GraphBolt, distributed tools, and DGL-Go workflows.

majiayu000/claude-skill-registry

Use the LoRA repository and loralib package to add low-rank adapters to PyTorch modules, fine-tune RoBERTa or DeBERTa on GLUE tasks, or reproduce the repository's GPT-2 data-to-text workflows.

majiayu000/claude-skill-registry

Guide for building Graph Neural Networks with PyTorch Geometric (PyG).

BioTender-max/awesome-bio-agent-skills

27 ai & machine learning skills. An agent skill from wentorai/research-plugins.

wentorai/research-plugins

AI 模型文件逆向与静态分析：ONNX/PyTorch/Safetensors/TFLite 格式解析、 网络结构还原、权重提取、文件级水印分析（权重 pattern/metadata/tensor hash/embedding 异常）。

dslsdzc/rev-skills

Implements federated learning architecture patterns for GDPR compliance.

mukul975/Privacy-Data-Protection-Skills

UMAP dimensionality reduction for visualization, clustering prep, and feature engineering.

jaechang-hits/SciAgent-Skills

使用本地 BiRefNet GGUF 模型完成图片或视频抠图、人物抠图、主体分割和背景移除，并输出透明 PNG、MOV 或 WebM。适用于用户提到图片抠图、照片去背景、人像透明图、视频抠图、透明视频、BiRefNet、JPG/PNG/BMP/WebP 图片，或 MP4/MOV/WebM 视频的场景；无需 Python、PyTorch 或 CUDA。

aiskillstore/marketplace

3D tetrahedral FEM modal analysis of a membrane STL. An agent skill from lamm-mit/scienceclaw.

lamm-mit/scienceclaw

Soft differentiable drop-in replacements for non-differentiable JAX functions (abs, relu, sort, argmax, comparison, logical operators, etc.) with adjustable softening strength.

lamm-mit/scienceclaw

Approximate deep learning model components with symbolic equations using PySR

lamm-mit/scienceclaw

Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration.

Kilo-Org/kilo-marketplace

Best practices for building, training, evaluating, and deploying neural networks with TensorFlow and Keras.

Mindrally/skills

Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment.

MicrosoftDocs/Agent-Skills