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A MMU system developed by ANNEX Engineering
Tetra Flow MMU (multi material unit) for 3d printers
Minimal reproduction of DeepSeek R1-Zero
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
An extension of the PyTorch library containing various tools for performing deep learning in hyperbolic space.
Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RI…
Python library to manipulate ESC/POS printers
Github code for the paper Maximum Class Separation as Inductive Bias in One Matrix. Arxiv link: https://arxiv.org/abs/2206.08704
Memory, Attention and Composition (MAC) Network for CLEVR/GQA implemented in PyTorch
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
A VGG-based perceptual loss function for PyTorch.
Overview of conditional computution and dynamic CNNs for computer vision, with a focus on reducing computational complexity
The official source code for the paper Consensus-Aware Visual-Semantic Embedding for Image-Text Matching (ECCV 2020)
Examples of using Python for Twitter social data mining, using the python-twitter-tools framework.
Control WS2812B and many more types of digital RGB LEDs with an ESP32 over WiFi!
Kunena Forum - Forum / Bulletin Board / Discussions component for Joomla - This is the 6.x/5.x main development branch. Please do not open issues regarding earlier versions of Kunena
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Semantic Segmentation : Multiclass fine tuning of DeepLabV3 with PyTorch
Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
Codebase for "Decoding language spatial relations to 2D spatial arrangements" (Findings of EMNLP 2020).