Awj2021

Awj2021's Stars

• coqui-ai/TTS

  🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

  Language:Python35.5k4.3k

• talkingnow/HM-Conformer

  Language:Python241

• grip-unina/poi-forensics

  POI-Forensics

  Language:Python555

• k2-fsa/icefall

  Language:Python934296

• PairCustomization/PairCustomization

  Language:Python915

• wangkai930418/DPL

  Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing (NeurIPS 2023)

  Language:Python905

• bbenligiray/nus_wide_formatter

  A tool to download and format NUS-WIDE dataset for multilabel classification

  Language:Python53

• sivannavis/samo

  SAMO: SPEAKER ATTRACTOR MULTI-CENTER ONE-CLASS LEARNING FOR VOICE ANTI-SPOOFING

  Language:Python359

• Purdue-M2/Robust_DM_Generated_Image_Detection

  Language:Python62

• 52CV/CVPR-2024-Papers

  82649

• qiuqiangkong/audioset_tagging_cnn

  Language:Python1.4k255

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook15.1k1.4k

• ljwztc/CLIP-Driven-Universal-Model

  [ICCV 2023] CLIP-Driven Universal Model; Rank first in MSD Competition.

  Language:Python58071

• facebookresearch/dino

  PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

  Language:Python6.4k911

• lucidrains/ema-pytorch

  A simple way to keep track of an Exponential Moving Average (EMA) version of your Pytorch model

  Language:Python51731

• Awj2021/psla

  Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".

  1

• YuanGongND/psla

  Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".

  Language:Python14016

• DeepMicroscopy/QuiltCleaner

  Automatic cleaning of the QUILT-1M pathology dataset

  Language:Jupyter Notebook3

• okaris/omni-zero

  A diffusers pipeline for zero shot stylised portrait creation

  Language:Python43723

• CreamyLong/stable-diffusion

  Speechless at the original stable-diffusion

  Language:Jupyter Notebook7211

• PathologyFoundation/plip

  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.

  Language:Python27527

• cccntu/fine-tune-models

  Language:Jupyter Notebook11012

• openai/consistencydecoder

  Consistency Distilled Diff VAE

  Language:Python2.1k76

• whlzy/FiT

  [ICML 2024 Spotlight] FiT: Flexible Vision Transformer for Diffusion Model

  Language:Python3899

• tencent-ailab/IP-Adapter

  The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt.

  Language:Jupyter Notebook5.3k336

• GuyTevet/motion-diffusion-model

  The official PyTorch implementation of the paper "Human Motion Diffusion Model"

  Language:Python3.2k343

• CompVis/taming-transformers

  Taming Transformers for High-Resolution Image Synthesis

  Language:Jupyter Notebook5.8k1.1k

• mlmed/torchxrayvision

  TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

  Language:Jupyter Notebook931218

• haofanwang/ControlNet-for-Diffusers

  Transfer the ControlNet with any basemodel in diffusers🔥

  Language:Python81348

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook68.4k10.2k