yuys0602

yuys0602's Stars

• RVC-Boss/GPT-SoVITS

  1 min voice data can also be used to train a good TTS model! (few shot voice cloning)

  Language:Python33.4k2041.2k3.8k

• hiyouga/LLaMA-Factory

  Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)

  Language:Python31.8k2034.9k3.9k

• lllyasviel/ControlNet

  Let us control diffusion models!

  Language:Python29.9k2175452.7k

• hpcaitech/Open-Sora

  Open-Sora: Democratizing Efficient Video Production for All

  Language:Python21.8k1854872.1k

• Mozilla-Ocho/llamafile

  Distribute and run LLMs with a single file.

  Language:C++19.4k175411984

• joonspk-research/generative_agents

  Generative Agents: Interactive Simulacra of Human Behavior

  16.3k1331262.1k

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook14.7k1103871.3k

• voicepaw/so-vits-svc-fork

  so-vits-svc fork with realtime support, improved interface and more features.

  Language:Python8.7k673601.2k

• niedev/RTranslator

  Open source real-time translation app for Android that runs locally

  Language:C++6.6k5055495

• modelscope/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.

  Language:Python6.2k581.1k657

• Blealtan/efficient-kan

  An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

  Language:Python3.9k3638350

• microsoft/torchscale

  Foundation Architecture for (M)LLMs

  Language:Python3k4677202

• YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy

  Diffusion model papers, survey, and taxonomy

  2.9k538247

• KevinWang676/Bark-Voice-Cloning

  Bark Voice Cloning and Voice Cloning for Chinese Speech

  Language:Jupyter Notebook2.7k3397395

• Gourieff/sd-webui-reactor

  Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111 SD WebUI, SD WebUI Forge, SD.Next, Cagliostro)

  Language:Python2.5k29338264

• jeinlee1991/chinese-llm-benchmark

  中文大模型能力评测榜单：目前已囊括115个大模型，覆盖chatgpt、gpt4o、百度文心一言、阿里通义千问、讯飞星火、商汤senseChat、minimax等商用模型， 以及百川、qwen2、glm4、yi、书生internLM2、llama3等开源大模型，多维度能力评测。不仅提供能力评分排行榜，也提供所有模型的原始输出结果！

  2.5k3346119

• Tencent/MimicMotion

  High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance

  Language:Python1.7k2887138

• GistNoesis/FourierKAN

  Language:Python6908757

• ga642381/speech-trident

  Awesome speech/audio LLMs, representation learning, and codec models

  61832227

• owenliang/qwen-vllm

  通义千问VLLM推理部署DEMO

  Language:Python4145758

• ControlNet/MARLIN

  [CVPR] MARLIN: Masked Autoencoder for facial video Representation LearnINg

  Language:Python22292420

• YoMio-Tech-Inc/GPT-SoVITS2

  GPT-SoVITS2

  Language:Python17113

• happyapplehorse/agere

  The tool is used for building and driving workflows specifically tailored for AI initiatives. It can be used to construct AI agents.

  Language:Python1245112

• tjuHaoXiaotian/pymarl3

  We extend pymarl2 to pymarl3, equipping the MARL algorithms with permutation invariance and permutation equivariance properties. The enhanced algorithm achieves 100% win rates on SMAC-V1 and superior performance on SMAC-V2.

  Language:Python12331112

• YangLing0818/RealCompo

  [NeurIPS 2024] RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models

  Language:Python104433

• YuchuanTian/AIGC_text_detector

  [ICLR'24 Spotlight] The official codes of our work on AIGC detection: "Multiscale Positive-Unlabeled Detection of AI-Generated Texts"

  Language:Python981815

• BAAI-Agents/GPA-LM

  This repo is a live list of papers on game playing and large multimodality model - "A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges".

  91414

• syassami/FourierKAN-mnist

  MNIST example using Kolmogorov-Arnold Networks

  Language:Python25102

• THU-KEG/WaterBench

  [ACL2024-Main] Data and Code for WaterBench: Towards Holistic Evaluation of LLM Watermarks

  Language:Python18101

• 123latiao/Apriori

  购物篮关联规则挖掘主要步骤如下: 1.对原始数据进行数据探索性分析,分析商品的热销情况与商品结构。 2.对原始数据进行数据预处理，转换数据形式，使之符合Apriori关联规则算法要求。 3.在步骤2得到的建模数据基础上，采用Apriori关联规则算法,调整模型输入参数,完成商品关联性分析。 4.结合实际业务,对模型结果进行分析,根据分析结果给出销售建议,最后输出关联规则结果。

  Language:Jupyter Notebook4