polyglot-integration
Integrate multiple programming languages using FFI, native bindings, gRPC, or language bridges. Use when combining strengths of different languages or integrating legacy systems.
浏览 benchflow-ai 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
349收录技能的仓库 Stars 合计
183,468仓库 Forks
66,973平均每个技能的仓库 Stars
526同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Integrate multiple programming languages using FFI, native bindings, gRPC, or language bridges. Use when combining strengths of different languages or integrating legacy systems.
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch...
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...
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...
Microsoft Pragmatic Rust FFI Guidelines. Use when working with C/C++ interop, creating cdylib, writing unsafe FFI code, or multi-DLL Rust projects.
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in
ML inference latency optimization, model compression, distillation, caching strategies, and edge deployment patterns. Use when optimizing inference performance, reducing model size, or deploying ML at the edge.
LLM inference infrastructure, serving frameworks (vLLM, TGI, TensorRT-LLM), quantization techniques, batching strategies, and streaming response patterns. Use when designing LLM serving infrastructure, optimizi...
Build RAG systems, semantic search, and document clustering with Gemini embeddings API (gemini-embedding-001). Generate 768-3072 dimension embeddings for vector search, integrate with Cloudflare Vectorize, and...
Analyze videos using Google's Gemini API - describe content, answer questions, transcribe audio with visual descriptions, reference timestamps, clip videos, and process YouTube URLs. Supports 9 video formats, m...
Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing...
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal...
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
Reduces LLM costs and improves response times through caching, model selection, batching, and prompt optimization. Provides cost breakdowns, latency hotspots, and configuration recommendations. Use for "cost re...
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory....
Invoke this skill BEFORE implementing any text extraction/parsing logic to learn how to use LlamaParse to process any document accurately. Requires llama_cloud_services package and LLAMA_CLOUD_API_KEY as an env...
Validate datasets for Unsloth fine-tuning. Use when the user wants to check a dataset, analyze tokens, calculate Chinchilla optimality, or prepare data for training.
Comprehensive toolkit for interacting with Hugging Face Spaces. Use this skill when working with Hugging Face Spaces - listing spaces, retrieving space information, managing space runtime (restart/pause), check...
Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch....
Design and implement RESTful API endpoints following REST principles with consistent naming conventions, proper HTTP methods, versioning strategies, and appropriate status codes. Use this skill when creating ne...
Modern Python 3.12+ development with uv, ruff, pydantic, FastAPI, async patterns, and production-ready practices.
Generates nginx-sites-available-default configuration file for serving the Vue application on Debian/Ubuntu-based nginx installations.
Configure Nginx web server for high-performance reverse proxy, load balancing, SSL/TLS, caching, and API gateway functionality.
**IMPORTANT**: Any change to React or Next.js code must read through this skill first. React and Next.js guidelines from Vercel Engineering covering visual instability, layout shifts, CLS, flickering, hydration...
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。