Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds
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Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds
Generate Pydantic v2 models, dataclasses, TypedDict, and msgspec.Struct from OpenAPI, JSON Schema, GraphQL, Avro, Protobuf, and raw JSON/YAML/CSV.
Superfast AI decision making and intelligent processing of multi-modal data.
Vector (and Scalar) Quantization, in Pytorch
A Python library for building AI agents that leverage the full power of Google Antigravity.
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等),7位分析师基于A股规则的辩论决策,基于TradingAgents深度改造,适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。
State-of-the-art LLM compression, built for production inference with vLLM
[ICLR2025 Spotlight] SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
[ICML'26] SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal
Vizro is a low-code toolkit for building high-quality data visualization apps.
Loki - Simple IOC and YARA Scanner
De-AI writing skill for any Agent Skills-compatible agent (77+ via the Skills CLI), with native plugins for Claude Code, Codex, Grok Build, and Antigravity. Narrative-architecture repair for fiction, venue-matched rules for professional prose. Based on StoryScope (arXiv:2604.03136).
A plugin for AI coding agents (Antigravity, Claude Code) enabling Spec-Driven Development to specify, plan, and implement software features.
awesome game security [Welcome to PR]
Official PyTorch implementation of SegFormer
Algorithmic Trading in Python with Machine Learning
A Python module to bypass Cloudflare's anti-bot page.
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
TranslatedAgent Skill for Refining AI-Generated Japanese into Natural Japanese
Self-hosted platform to unify wearable health data through one AI-ready API.
Asynchronous Python ODM for MongoDB
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn