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AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for bette…
📝 لیست وبلاگهای فارسیزبان در حوزههای مختلف
A Python implementation of the JSON5 data format
Cambrian-1 is a family of multimodal LLMs with a vision-centric design.
MiniCPM-V 4.5: A GPT-4o Level MLLM for Single Image, Multi Image and High-FPS Video Understanding on Your Phone
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
a state-of-the-art-level open visual language model | 多模态预训练模型
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
PyTorch code and models for V-JEPA self-supervised learning from video.
fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing d…
A game theoretic approach to explain the output of any machine learning model.
Python composable command line interface toolkit
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
🔴 1704 Machine Learning, Data Science & Python Interview Questions (ANSWERED) To Kill Your Next ML & DS Interview. Get All Answers + PDFs on MLStack.Cafe. Post your ML Jobs 👉
🦜🔗 The platform for reliable agents.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Accessible large language models via k-bit quantization for PyTorch.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
[ICLR 2023 Spotlight] Vision Transformer Adapter for Dense Predictions
PyTorch code and models for the DINOv2 self-supervised learning method.