Pinned Repositories
AdvSemiSeg
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
asv-subtools
An Open Source Tools for Speaker Recognition
AutoGAN
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
AutoML
AutoDeeplab / auto-deeplab / AutoML for semantic segmentation, implemented in Pytorch
awesome-data-valuation
💱 A curated list of data valuation (DV) to design your next data marketplace
awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
awesome-lane-detection
lane detection
Awesome-LLM-Inference
📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.
datasets
Collections of many datasets you may need and play with.
GE2E-SV-TI-CHINESE-LMS-FINAL
ABexit's Repositories
ABexit/asv-subtools
An Open Source Tools for Speaker Recognition
ABexit/awesome-data-valuation
💱 A curated list of data valuation (DV) to design your next data marketplace
ABexit/Awesome-LLM-Inference
📖A curated list of Awesome LLM Inference Paper with codes, TensorRT-LLM, vLLM, streaming-llm, AWQ, SmoothQuant, WINT8/4, Continuous Batching, FlashAttention, PagedAttention etc.
ABexit/awesome-machine-learning-interpretability
A curated list of awesome machine learning interpretability resources.
ABexit/awesome-mixture-of-experts
A collection of AWESOME things about mixture-of-experts
ABexit/CRATE
Code for CRATE (Coding RAte reduction TransformEr).
ABexit/DeepSpeaker_RawNet_GE2E
分别在VCTK、AISHELL1 和 VoxCeleb1 三个标准公开数据集上对三种端到端声纹模型框架（Deep Speaker, RawNet, GE2E）进行实验比较。
ABexit/Diffusion-Models-Papers-Survey-Taxonomy
Diffusion model papers, survey, and taxonomy
ABexit/DomainBed
DomainBed is a suite to test domain generalization algorithms
ABexit/editGAN_release
ABexit/ENet-SAD_Pytorch
Pytorch implementation of "Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)"
ABexit/fairseq-fackbook
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
ABexit/FunASR
A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.
ABexit/GPT-SoVITS
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
ABexit/LibFewShot
LibFewShot: A Comprehensive Library for Few-shot Learning.
ABexit/MiniCPM
MiniCPM-2B: An end-side LLM outperforms Llama2-13B.
ABexit/MobileFormer
MobileFormer in torch
ABexit/ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ABexit/NeuralSpeech
ABexit/nn_interpretability
Pytorch implementation of various neural network interpretability methods
ABexit/NoisySpeakerDetection
Detect mislabeled speaker ID
ABexit/real-world-sr
[ICCVW 2019] PyTorch implementation of DSGAN and ESRGAN-FS from the paper "Frequency Separation for Real-World Super-Resolution". This code was the winning solution of the AIM challenge on Real-World Super-Resolution at ICCV 2019
ABexit/RealSR
Real-World Super-Resolution via Kernel Estimation and Noise Injection
ABexit/so-vits-svc-fork
so-vits-svc fork with realtime support, improved interface and more features.
ABexit/StyleSpace
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
ABexit/torch-cam
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
ABexit/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
ABexit/TTS
:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
ABexit/unilm-microsoft
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
ABexit/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch