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.

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.

[ICLR 2025] Autoregressive Video Generation without Vector Quantization

TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab.

Implementation of RQ Transformer, proposed in the paper "Autoregressive Image Generation using Residual Quantization"