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121–144 of 178 · Most stars

A Python native dynamical system simulation framework in the block diagram paradigm.

  • blockdiagram
  • control-systems
  • hierarchical-modeling
  • nonlinear-dynamics

Scaling in Games: Continued Pre-Training for Embodied Agents in Diverse Virtual Worlds. Weights on Hugging Face.

  • embodied-agent
  • game-agent
  • game-ai
  • mihoyo

Code and Pretrained Models for Interspeech 2023 Paper "Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong Audio Event Taggers"

  • audio
  • audio-classification
  • audio-processing
  • audio-tagging

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

NNDial is an open source toolkit for building end-to-end trainable task-oriented dialogue models. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

[ECCV 2026] Official implementation of "HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Models"

[arXiv 2026] Unified Audio-Video Creation via Progressive Training and Asymmetric Scheduling

  • audio-to-video
  • joint-audio-video-generation
  • unified-model
  • video-to-audio

Battle-tested agent skills for Product Builders. Part of the Product Builder OS by Superhero.tech: Super Brain for context, skills for action, built from 32+ years of combined product experience and pressure-tested with 1,800 builders.

INGInious is a secure and automated exercises assessment platform using your own tests, also providing a pluggable interface with your existing LMS.