Interpretability and explainability of data and machine learning models
- explainable-ai
- explainable-ml
- trusted-ai
- trusted-ml
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Interpretability and explainability of data and machine learning models
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
OpenMMLab Foundational Library for Training Deep Learning Models
Open-source GNSS + inertial navigation, sensor fusion simulator. Motion trajectory generator, sensor models, and navigation
We propose Prism, a dynamic sparse attention framework for natively training joint video-audio generation models at 2K.
Translates Django models using a registration approach.
No-code in the front, Python in the back. An open-source framework for creating data apps.
Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.
GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard | Fable 5 Level Coding for a Fifth the Price - or on a Single GPU
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
A clinical decision-evidence benchmark: pull the one fact an answer rests on, and see whether the assistant's action moves with the evidence. Built on HealthBench.
AssetFurnace: the most complete open-source image-to-3D pipeline (Oct 2026). Prompt or picture → textured, rigged, animated game character, locally on Apple Silicon or NVIDIA. Pixal3D, TRELLIS.2, Hunyuan3D, SF3D, auto-rig and 21 moves. For indie game devs and 3D artists. Free, Apache-2.0.
Upscale an image by a factor of 4, while generating photo-realistic details.
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python
allRank is a framework for training learning-to-rank neural models based on PyTorch.
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
EdgeRock: Strong Reasoning at Constant Memory. Multimodal models with O(N) generation and O(1) persistent history. Inference and evaluation code.
Native vLLM serving for Jev decision models
Scenario for Blender: AI images, video, 3D and PBR materials in the viewport, plus a local MCP server for agents. Blender 5.0+ extension, GPL-3.0-or-later.