GitHub
rust-coder
Rust expert for rainze_core PyO3 module. Use when working on Rust code, performance-critical components, or Python-Rust FFI.
☆ 0查看技能
tools framework internals AI 技能
发现 tools framework internals 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
分类目录: tools framework internals
tools framework internals 清除筛选
全部技能
GitHub
rust-expert
Expert Rust development including ownership, lifetimes, async, and systems programming
☆ 0查看技能
GitHub
architect
Expert guidance for GabeDA v2.1 architecture (34 modules) - implementing models, features, debugging 4-case logic, and maintaining the /src codebase.
☆ 0查看技能
GitHub
netninja-qt-compat
Implement and maintain NET-NiNJA's Qt compatibility logic: auto-select PyQt6 vs PyQt5 based on CPU features (SSE4.1/4.2), add and honor --gui=auto|qt6|qt5, and prevent premature PyQt6 imports that crash on lega...
☆ 0查看技能
GitHub
skill-with-scripts
A template for skills that include executable code for deterministic operations.
☆ 0查看技能
GitHub
root-calculator
Performs mathematical root calculations including square root, cube root, and nth roots. Use when user asks to calculate square root, cube root, nth root, or uses keywords like 'sqrt', 'root of', 'calculate roo...
☆ 0查看技能
GitHub
pytorch-cuda
PyTorch CUDA environment and performance guidance, with emphasis on CUDA 13 toolkit/driver requirements, PyTorch wheel compatibility, and runtime checks. Use when configuring PyTorch on NVIDIA GPUs, debugging C...
☆ 0查看技能
GitHub
numpy-masked
Masked arrays for robust handling of missing or invalid data, ensuring they are excluded from statistical and mathematical computations. Triggers: masked array, numpy.ma, missing data, invalid values, hard mask...
☆ 0查看技能
GitHub
unsloth-qlora
Advanced 4-bit quantization techniques using Unsloth and BitsAndBytes for extreme VRAM efficiency (triggers: QLoRA, 4-bit, load_in_4bit, bnb-4bit, VRAM optimization, dynamic quantization).
☆ 0查看技能
GitHub
pytorch-core
Core PyTorch fundamentals including tensor operations, autograd, nn.Module architecture, and training loop orchestration. Covers optimizations like pin_memory and lazy module initialization. (pytorch, tensor, a...
☆ 0查看技能
GitHub
pytorch-quantization
Techniques for model size reduction and inference acceleration using INT8 quantization, including Post-Training Quantization (PTQ) and Quantization Aware Training (QAT). (quantization, int8, qat, fbgemm, qnnpac...
☆ 0查看技能
GitHub
torch-compile
Optimize PyTorch with torch.compile (TorchDynamo/Inductor), focusing on compile overhead, graph breaks, and benchmark methodology. Use when speeding up PyTorch models or debugging compile behavior; triggers: to...
☆ 0查看技能
GitHub
pytorch-onnx
Exporting PyTorch models to ONNX format for cross-platform deployment. Includes handling dynamic axes, graph optimization in ONNX Runtime, and INT8 model quantization. (onnx, onnxruntime, torch.onnx.export, dyn...
☆ 0查看技能
GitHub
numpy-core
Fundamental NumPy operations including ndarray creation, dtypes, shape manipulation, and basic operations with a focus on memory alignment and data views. Triggers: numpy, ndarray, dtype, reshape, memory alignm...
☆ 0查看技能
GitHub
unsloth-quantization
Utilizing Dynamic 4-bit quantization, FP8 training, and 8-bit optimizers to minimize VRAM usage without sacrificing accuracy. Triggers: quantization, dynamic 4-bit, fp8, bitsandbytes, adamw_8bit, qat.
☆ 0查看技能
GitHub
pytorch-distributed
Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers multi-node setup, checkpointing, and process management using torchrun. (ddp, fsdp, distrib...
☆ 0查看技能
GitHub
numpy-memory
Deep dive into memory layout, including strides, C vs Fortran order, and zero-copy view generation via stride tricks. Triggers: strides, C-order, Fortran-order, memory locality, stride_tricks.
☆ 0查看技能
GitHub
numpy-ufuncs
Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.
☆ 0查看技能
GitHub
numpy-structured
Structured and record arrays for C-interoperability, binary blob interpretation, and multi-field tabular data handling. Triggers: structured array, record array, compound dtype, multi-field index.
☆ 0查看技能
GitHub
numpy-interop
Protocols for cross-library data exchange including DLPack, buffer interfaces, and __array_ufunc__ for overriding NumPy functions. Triggers: DLPack, interoperability, __array_interface__, __array_ufunc__, buffe...
☆ 0查看技能
GitHub
torchvision
Computer vision library for PyTorch featuring pretrained models, advanced image transforms (v2), and utilities for handling complex data types like bounding boxes and masks. (torchvision, transforms, tvtensor,...
☆ 0查看技能
GitHub
discoverymarket-scan
Analyze the competitive and adjacent solution landscape to surface differentiation opportunities.
☆ 0查看技能
GitHub
my-skill
A custom skill that helps with specific tasks in my project
☆ 0查看技能
GitHub
sensor-integration
Generate production-quality Python code for sensor integration, sensor fusion, and perception systems that run in Pyodide (browser). Creates educational code for teaching IMU sensors, LiDAR simulation, depth pe...
☆ 0查看技能
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。