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找到 923 个相关结果 / 搜索与检索

研究学习 / 检索整理

axiom-apple-docs-research

axiom-apple-docs-research

204

Use when researching Apple frameworks, APIs, or WWDC sessions - provides techniques for retrieving full transcripts, code samples, and documentation using…

Stars 902
uiapiaxiomapple

研究学习 / 检索整理

design-postgres-tables

design-postgres-tables

204

Use this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables **Keywords:** PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices.

Stars 1,729
designuiperformancesecurity

研究学习 / 检索整理

qdrant-vector-search

qdrant-vector-search

203

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search,…

Stars 8,486
uiperformancedeploymentdatabase

研究学习 / 检索整理

embedding-strategies

embedding-strategies

203

Guide to selecting and optimizing embedding models for vector search applications.

Stars 37,677
uiembeddingstrategiesguide

研究学习 / 检索整理

knowledge-distillation

knowledge-distillation

203

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance,…

Stars 8,478
performancellmknowledgedistillation

研究学习 / 检索整理

llamaindex

llamaindex

203

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices,…

Stars 8,478
uiragllmllamaindex

研究学习 / 检索整理

llamaguard

llamaguard

202

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm,…

Stars 8,478
uillmllamaguardmeta

研究学习 / 检索整理

nemo-guardrails

nemo-guardrails

202

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII…

Stars 8,482
uillmnemoguardrails

研究学习 / 检索整理

octocode-research

octocode-research

202

Use when the user asks to "research code", "how does X work", "where is Y defined", "who calls Z", "trace code flow", "find usages", "explore this library",…

Stars 831
uioctocoderesearchthe

研究学习 / 检索整理

sentence-transformers

sentence-transformers

202

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval.…

Stars 8,487
apiraggithubsentence

研究学习 / 检索整理

memory-protocol

memory-protocol

201

Persistent cross-session memory using Memento MCP knowledge graph (mcp__memento__* tools). Recall-before-acting: search memory before starting tasks, on errors, and when receiving corrections. Multi-dimensional search: two queries per recall event (technical topic + process/workflow learnings). Store-after-discovery: persist solutions, conventions, and corrections immediately. Three-step recall: search, open_nodes, traverse relations. WORKING_STATE.md for crash recovery. Self-reminder protocol every 5-10 messages. Activate on task start, errors, corrections, session boundaries, or explicit memory requests. See references/agents-md-setup.md for AGENTS.md integration.

Stars 2
agentagentsworkflowdebugging

研究学习 / 检索整理

hqq-quantization

hqq-quantization

201

Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast…

Stars 8,475
backendllmhqqquantization

研究学习 / 检索整理

亚马逊关键词研究

amazon-keyword-research

201

亚马逊关键词研究与市场机会分析,面向卖家。获取自动补全建议(长尾关键词),分析竞争对手格局,以及…

Stars 0
apiragamazonkeyword

研究学习 / 检索整理

speculative-decoding

speculative-decoding

201

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6×…

Stars 8,489
llmspeculativedecodingaccelerate

研究学习 / 检索整理

pyvene-interventions

pyvene-interventions

201

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing,…

Stars 8,486
uigithubpyveneinterventions

研究学习 / 检索整理

grpo-rl-training

grpo-rl-training

201

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

Stars 8,475
uiworkflowgrpotraining

研究学习 / 检索整理

openrlhf-training

openrlhf-training

201

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2×…

Stars 8,482
uiperformancedockerllm

研究学习 / 检索整理

nemo-curator

nemo-curator

201

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics),…

Stars 8,482
performancellmnemocurator

研究学习 / 检索整理

dspy

dspy

201

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's…

Stars 8,474
uiragpromptagent

研究学习 / 检索整理

instructor

instructor

200

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream…

Stars 8,476
apillmgithubinstructor

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