Topic · AI & LLM Engineering
Best deep learning skills, page 7
Deep learning skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 289 | 289.Grpo Reference for the GRPO (Group Relative Policy Optimization) algorithm. | benchflow-ai/ | 1.8k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | 2 mo ago |
| 290 | Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. | majiayu000/ | 666 | 2 repos | ~1.6k | Automated safety check: Pass | MIT | today |
| 291 | Analyzes data-independent acquisition (DIA) proteomics by scoring reconstructed fragment-chromatogram peak groups against a decoy null with DIA-NN (library-free directDIA, library-based, or… | GPTomics/ | 1.2k | 1 repo | ~5.4k | Automated safety check: Pass | MIT | 1 mo ago |
| 292 | Predicts RNA secondary structure with ViennaRNA, treating the Boltzmann ensemble (partition function, base-pair probabilities, centroid, MEA, stochastic samples) as the object rather than a single… | GPTomics/ | 1.2k | 1 repo | ~5.9k | Automated safety check: Pass | MIT | 1 mo ago |
| 293 | Apply existing ShapeShifter graph passes to an .onnx model via the quark-cli shapeshifter CLI or a ShapeShifter YAML. | amd/ | 181 | — | ~1.9k | Automated safety check: Pass | MIT | 10 days ago |
| 294 | Diagnose failed Quark installation, PTQ execution, script generation, or export attempts. | amd/ | 181 | — | ~1.9k | Automated safety check: Notes | MIT | 10 days ago |
| 295 | Install or verify the correct PyTorch build for a user's accelerator backend before Quark installation. | amd/ | 181 | — | ~1.6k | Automated safety check: Pass | MIT | 10 days ago |
| 296 | L3 recipe that runs a Torch LLM PTQ end-to-end for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize → validate → evaluate. | amd/ | 181 | — | ~2.6k | Automated safety check: Pass | MIT | 10 days ago |
| 297 | Sub-skill técnica de Yann LeCun. An agent skill from majiayu000/claude-skill-registry. | majiayu000/ | 666 | 3 repos | ~4k | Automated safety check: Pass | MIT | today |
| 298 | 298.Sandbox Tfjs Classify and embed images, detect objects, and answer from a passage in a Code node or CodeAct action, with TensorFlow.js running on the host | nodetool-ai/ | 556 | — | ~660 | Automated safety check: Pass | AGPL-3.0 | today |
| 299 | Work with hyperspectral and multispectral images in MATLAB. An agent skill from matlab/matlab-agentic-toolkit. | matlab/ | 1.1k | — | ~3.7k | Automated safety check: Pass | Unknown | yesterday |
| 300 | Generate C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. | matlab/ | 1.1k | — | ~2.8k | Automated safety check: Pass | Unknown | yesterday |
| 301 | Creates MATLAB interfaces to Python image processing and computer vision models from GitHub repositories or pip-installable packages using MPyReq. | matlab/ | 1.1k | — | ~3.7k | Automated safety check: Pass | Unknown | yesterday |
| 302 | Load this first for any task involving images, pictures, photos, scans, frames, volumes, or visual data — including reading, writing, filtering, enhancing, denoising, sharpening, deblurring… | matlab/ | 1.1k | — | ~3.7k | Automated safety check: Pass | Unknown | yesterday |
| 303 | Validate Triton-Ascend kernel outputs against PyTorch references with dtype-aware tolerances, exact integer checks, bfloat16 promotion, and boolean handling. | Krusty84/ | 106 | — | ~649 | Automated safety check: Pass | Apache-2.0 | 1 mo ago |
| 304 | Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use only when the request names… | NVIDIA/ | 3.5k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 305 | Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use when the user names plain PyTorch or… | NVIDIA/ | 3.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | yesterday |
| 306 | This skill provides guidance for implementing PyTorch pipeline parallelism for distributed training of large language models. | lazyFrogLOL/ | 128 | — | ~2.1k | Automated safety check: Pass | No licence | 4 mo ago |
| 307 | This skill provides guidance for implementing tensor parallelism in PyTorch, specifically column-parallel and row-parallel linear layers. | lazyFrogLOL/ | 128 | — | ~2.8k | Automated safety check: Pass | No licence | 4 mo ago |
| 308 | Extract Intel GPU ISA (assembly) from any XPU kernel. An agent skill from intel/torch-xpu-ops. | intel/ | 115 | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | today |
| 309 | A skill your agent uses when setting up a new torch-xpu-ops release branch corresponding to a PyTorch release. | intel/ | 115 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | today |
| 310 | Build PyTorch from source with Intel XPU (GPU) support. An agent skill from intel/torch-xpu-ops. | intel/ | 115 | — | ~939 | Automated safety check: Pass | Apache-2.0 | today |
| 311 | Generate PyTorch release notes worksheet for XPU by searching git log between release branches. | intel/ | 115 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | today |
| 312 | 312.Quark Install Installs or verifies AMD Quark and ensures the selected Python environment has an accelerator-matched PyTorch. | amd/ | 181 | — | ~3.5k | Automated safety check: Notes | MIT | 10 days ago |
| 313 | 313.Quark Torch Ptq Runs an end-to-end AMD Quark post-training quantization workflow for PyTorch / Hugging Face LLMs: inspect a Hub or local model, choose a quantization plan, create reproducible artifacts, request… | amd/ | 181 | — | ~2.3k | Automated safety check: Pass | MIT | 10 days ago |
| 314 | Create efficient data pipelines with tf.data. An agent skill from TheBushidoCollective/han. | TheBushidoCollective/ | 198 | 2 repos | ~4.4k | Automated safety check: Notes | Unknown | 1 mo ago |
| 315 | Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). | NVIDIA/ | 3.5k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 316 | Generate and analyze T1/T2/R roofline reports for PyTorch OOB workloads comparing Intel XPU and NVIDIA CUDA. | intel/ | 115 | — | ~681 | Automated safety check: Pass | Apache-2.0 | today |
| 317 | Find upstream PyTorch behavior or fixes that may require XPU parity work, validate them on XPU, and produce independently reviewed evidence. | intel/ | 115 | — | ~2k | Automated safety check: Pass | Apache-2.0 | today |
| 318 | 318.Data Specialist 提供数据库设计、优化、数据工程和数据分析能力。当需要处理数据库操作、数据管道或数据分析时使用. An agent skill from Prorise-cool/Claude-Code-Multi-Agent. | Prorise-cool/ | 305 | — | ~1k | Automated safety check: Pass | No licence | 22 days ago |
| 319 | Predict LC-MS/MS (MS2, tandem mass spectra) from SMILES via ICEBERG, a two-stage deep neural network. | learningmatter-mit/ | 176 | — | ~1.6k | Automated safety check: Pass | MIT | today |
| 320 | 320.Chem Nmr Predict Predict 1H NMR spectra from SMILES strings via NMRdb.org SPINUS neural network prediction and nmrsim quantum mechanical spin simulation. | learningmatter-mit/ | 176 | — | ~1.8k | Automated safety check: Pass | MIT | today |
| 321 | 321.Ilya Sutskever Agente que simula Ilya Sutskever — co-fundador da OpenAI, ex-Chief Scientist, fundador da SSI. | majiayu000/ | 666 | 3 repos | ~15k | Automated safety check: Pass | MIT | today |
| 322 | 322.Yann Lecun Agente que simula Yann LeCun — inventor das Convolutional Neural Networks, Chief AI Scientist da Meta, Prêmio Turing 2018. | majiayu000/ | 666 | 3 repos | ~15k | Automated safety check: Pass | MIT | today |
| 323 | 323.Nanogpt Training Train GPT-2 scale models (~124M parameters) efficiently on a single GPU. | benchflow-ai/ | 1.8k | — | ~882 | Automated safety check: Pass | Apache-2.0 | 2 mo ago |
| 324 | 324.Scholar Compute Design and execute computational social science analyses across 11 modules: text-as-data/NLP (STM, BERTopic, Wordfish, BERT, conText embedding regression, LLM annotation + DSL bias correction… | joshzyj/ | 168 | — | ~15k | Automated safety check: Pass | Unknown | 20 days ago |
| 325 | Classical ML in Python: classification, regression, clustering, dim reduction, evaluation, tuning, preprocessing pipelines. | jaechang-hits/ | 370 | 1 repo | ~4k | Automated safety check: Pass | BSD-3-Clause | 9 days ago |
| 326 | PyTorch Geometric (PyG) for graph neural networks: node/graph classification, link prediction with GCN, GAT, GraphSAGE, GIN. | jaechang-hits/ | 370 | 1 repo | ~5.1k | Automated safety check: Pass | MIT | 9 days ago |
| 327 | 通过 PyTorch torch.distributed 接口测试昇腾 NPU 通信算子性能。支持指定任意 tensor shape、dtype,使用 torchrun 启动,贴近真实训练场景的通信算子测试与性能分析。Use for testing collective communication operators (AllReduce, AllGather, ReduceScatter… | ascend-ai-coding/ | 174 | — | ~2.2k | Automated safety check: Pass | No licence | today |
| 328 | 328.Domain ML A skill your agent uses when building ML/AI apps in Rust. An agent skill from majiayu000/claude-skill-registry. | majiayu000/ | 666 | 1 repo | ~1.2k | Automated safety check: Pass | MIT | today |
| 329 | Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). | majiayu000/ | 666 | 1 repo | ~4.6k | Automated safety check: Pass | MIT | today |
| 330 | Train, evaluate, and export neural networks to Simulink in MATLAB. | majiayu000/ | 666 | 1 repo | ~4.9k | Automated safety check: Pass | MIT | today |
| 331 | 331.Pyhealth Build clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality… | majiayu000/ | 666 | 1 repo | ~1.8k | Automated safety check: Pass | MIT | today |
| 332 | 332.Glm Use this model doc whenever the user wants to run a classical General Linear Model (GLM) for task-evoked fMRI activation analysis. | majiayu000/ | 666 | 1 repo | ~1.4k | Automated safety check: Pass | MIT | today |
| 333 | 333.Ibgnn Use this model doc whenever the user wants to run IBGNN (Interpretable Brain Graph Neural Network) for fMRI phenotype prediction. | majiayu000/ | 666 | 1 repo | ~1.1k | Automated safety check: Pass | MIT | today |
| 334 | 334.Ica Use this model doc whenever the user wants to perform resting-state network decomposition using ICA. | majiayu000/ | 666 | 1 repo | ~1.1k | Automated safety check: Pass | MIT | today |
| 335 | 335.Svm Use this model doc whenever the user wants to perform disease classification with SVM. | majiayu000/ | 666 | 1 repo | ~1k | Automated safety check: Pass | MIT | today |
| 336 | 优化实际模型推理链路,将正确性对齐、分段 profiling、显存与数据搬运、TensorRT/ONNX/PyTorch 后端、attention/kernel、FP8/compile、缓存与少步采样、质量回归、GPU 成本和服务验收串成同一实验闭环。当用户要求推理提速、降低显存或 GPU 成本、复现模型效果、定位 GPU 利用率低、优化图像/视频/扩散模型或自托管 LLM 时使用,提供… | majiayu000/ | 286 | — | ~1.1k | Automated safety check: Pass | MIT | today |
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- Building AI agents563
- Embeddings386
- LLM inference and serving372
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- Fine-tuning309
- LLM evaluation308
- Speech recognition and synthesis308
- Structured output and tool calling276
- LLM cost and token optimization259
- LLM API integration255
- Model routing and gateways255
- LLM observability240
- LLM guardrails221
- Computer vision203
- Model hubs and datasets180
- GPU and accelerator computing176
- Diffusion and image models166
- Natural language processing131
- Reinforcement learning66
- AI interpretability23