jianliu-ml

jianliu-ml's Stars

• ggerganov/llama.cpp

  LLM inference in C/C++

  Language:C++64.1k5353.6k9.2k

• freqtrade/freqtrade

  Free, open source crypto trading bot

  Language:Python27.9k6304.6k6k

• haotian-liu/LLaVA

  [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

  Language:Python18.9k1591.5k2.1k

• karpathy/llama2.c

  Inference Llama 2 in one file of pure C

  Language:C17.1k1902182k

• THUDM/ChatGLM2-6B

  ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型

  Language:Python15.7k1356151.8k

• nerfstudio-project/nerfstudio

  A collaboration friendly studio for NeRFs

  Language:Python9.1k1151.6k1.2k

• speechbrain/speechbrain

  A PyTorch-based Speech Toolkit

  Language:Python8.5k1301.1k1.4k

• fishaudio/Bert-VITS2

  vits2 backbone with multilingual-bert

  Language:Python7.7k4601.1k

• IDEA-CCNL/Fengshenbang-LM

  Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。

  Language:Python4k56293372

• xiph/rnnoise

  Recurrent neural network for audio noise reduction

  Language:C4k150197886

• resemble-ai/Resemblyzer

  A python package to analyze and compare voices with deep learning

  Language:Python2.7k7482420

• DAMO-NLP-SG/Video-LLaMA

  [EMNLP 2023 Demo] Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

  Language:Python2.7k32155242

• Nate711/StanfordDoggoProject

  Stanford Doggo is an open source quadruped robot that jumps, flips, and trots!

  2.3k18854733

• DroidAITech/ROS-Academy-for-Beginners

  **大学MOOC《机器人操作系统入门》课程代码示例

  Language:CMake2.3k82143780

• asteroid-team/asteroid

  The PyTorch-based audio source separation toolkit for researchers

  Language:Python2.2k54218418

• SeanNaren/deepspeech.pytorch

  Speech Recognition using DeepSpeech2.

  Language:Python2.1k52503621

• GantMan/nsfw_model

  Keras model of NSFW detector

  Language:Python1.7k35130270

• dawnlh/awesome-low-light-image-enhancement

  This is a resouce list for low light image enhancement

  Language:MATLAB1.4k3422209

• facebookresearch/svoice

  We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.

  Language:Python1.2k2589176

• DUOMO/TransGPT

  Language:Python69962577

• JusperLee/Conv-TasNet

  Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement

  Language:Python40965476

• JusperLee/Dual-Path-RNN-Pytorch

  Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch

  Language:Python40046067

• tky823/DNN-based_source_separation

  A PyTorch implementation of DNN-based source separation.

  Language:Python28272548

• Miraclemarvel55/ChatGLM-RLHF

  对ChatGLM直接使用RLHF提升或降低目标输出概率|Modify ChatGLM output with only RLHF

  Language:Python1861726

• xuchenglin28/speaker_extraction

  target speaker extraction and verification for multi-talker speech

  Language:Python1538529

• BUTSpeechFIT/speakerbeam

  Language:Jupyter Notebook936318

• csukuangfj/kaldilm

  Python wrapper for kaldi's arpa2fst

  Language:C++384126

• farisalasmary/deepspeech2-online-decoder

  Online (real-time) decoder to be used with DeepSpeech2 model

  Language:Python24354

• Miraclemarvel55/LLaMA-MOSS-RLHF-LoRA

  用RLHF可选LoRA对LLaMA和MOSS进行训练|Training LLaMA or MOSS with RLHF [LoRA]

  Language:Python20231

• etzinis/optimal_condition_training

  Code and data recipes for the paper: Optimal Condition Training for Target Source Separation by Efthymios Tzinis, Gordon Wichern, Paris Smaragdis and Jonathan Le Roux

  Language:Python12101