Accessible large language models via k-bit quantization for PyTorch.

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

A curated set of agent skills for Qdrant vector search, providing structured knowledge on scaling, optimization, monitoring, deployment, and SDK usage.

Rust multi‑backend OCR/VLM engine (DeepSeek‑OCR-1/2, PaddleOCR‑VL, DotsOCR) with DSQ quantization and an OpenAI‑compatible server & CLI – run locally without Python.

Prepare a new release by collecting commits, generating bilingual release notes, updating version files, and creating a release branch with PR. Use when asked to prepare/create a release, bump version, or run `/prepare-release`.

Create branded architecture, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, Venn, pyramid/funnel, treemap, bar, line, Gantt and scatter charts, high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, deployment, dependency graph, UML class, story map, or database schema diagrams as standalone HTML/SVG/PNG. Redraw .drawio/.drawio.png/.drawio.svg or Mermaid .mmd sources at a chosen size/detail; onboard brand tokens from a website; add semantic patterns, callouts, accessible motion, or sketchy/hand-drawn styling.

Open finite element infrastructure for nonlinear computational mechanics.

Python package for solving partial differential equations using finite differences.

:gem: Feel++: Finite Element Embedded Language and Library in C++

PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

PMetal: high-performance Apple Silicon framework for local LLM inference, LoRA/QLoRA fine-tuning, serving, quantization, and MLX/Metal acceleration.

Implements GraphQL APIs in Golang using gqlgen or graphql-go. Apply when building GraphQL servers, designing schemas, writing resolvers, handling subscriptions, or integrating GraphQL with existing Go HTTP services. Also apply when the codebase imports `github.com/99designs/gqlgen` or `github.com/graph-gophers/graphql-go`.