samplers

An open-source toolbox for fast sampling of diffusion models. Official implementations of our works published in ICML'24, NeurIPS'24, CVPR'24, J. Stat. Mech'25.

Quasi-Monte Carlo sampling library for rendering and graphics applications.

🎥 Datasets, transforms and samplers for video in PyTorch

AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.

Upload and Download wav files to the EPS16+ Sampler

Euclidean Rhythms (polyrhythms) drum machine audio VST3 plugin

MongeNet sampler official implementation

Cross-platform CLI for inspecting, transforming, and writing E-MU E4/EIV sampler firmware (EOS).

Create MPC1000-compatible program files (.PGM) from audio samples. Slice audio files, assign them to pads, and export directly to your MPC1000.

ComfyUI suite: visual prompt + LoRA gallery (Library/Style/Multi), one-node Smart Detailer (face/eyes/hands/feet via YOLO + optional SAM, per-target cycles, min_detail_size gate, no Impact-Pack required), SDXL + Anima samplers w/ HiResFix, Civitai metadata writer, comic regional conditioning, wildcards. Zero ComfyUI custom-node deps.

SeaVoX Device Catalogue

Network traffic sampler Sketch Guided Sampling, Packet Sampling, Random Sampling, Fast Filtered Sampling, Selective Flow Sampling

MPC60 LDK - MPC60 LOOP, DELAY and KEYBOARD

A groovebox app with a range of synthesizers, samplers, and effects, and a focus on performances and loops

RISC OS disk image explorer for Roland 12-bit samplers.

Command line tool for working with Casio FZ series samplers

Brainwell.inc prototype version [isolated later]

This GitHub repository hosts a comprehensive JMeter Performance Testing Suite specifically tailored for evaluating the performance of demoqa.com. Leveraging Apache JMeter's powerful testing capabilities, this suite offers a structured approach to measure and analyze the performance metrics of the demoqa.com website.

3d printable files for hardware samplers & studio gear

A DDPM from scratch in one PyTorch file, on a 6GB laptop GPU — plus an honest sampler ablation: what actually buys sample quality, a better solver or better-placed steps?