pix2tex: Using a ViT to convert images of equations into LaTeX code.
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Nano vLLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
- attention-mechanism
- deep-learning
- gpt
- gpt-2
A very simple framework for state-of-the-art Natural Language Processing (NLP)
An open source implementation of CLIP.
- deep-learning
- pytorch
- computer-vision
- language-model
Convert Machine Learning Code Between Frameworks
- python
- tensorflow
- pytorch
- numpy
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
- reinforcement-learning
- reinforcement-learning-algorithms
- machine-learning
- gym
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
- gpt-2
- adaptation
- language-model
- gpt-3
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
- deep-learning
- pytorch
- grad-cam
- visualizations
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
- bert
- sentence-encoding
- deep-learning
- clip-model
🐍 Geometric Computer Vision Library for Spatial AI
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
- attention
- pytorch
- paper
- cbam
A collaboration friendly studio for NeRFs
A PyTorch-based Speech Toolkit
- speech-recognition
- speech-toolkit
- speaker-recognition
- speech-to-text
TranslatedPython open-source project "The Road to Self-Taught Programming", with step-by-step tutorials for beginners: AI Lab, treasure videos, data structures, study guides, hands-on machine learning, hands-on deep learning, web crawlers, big-company interview experiences, programmer life, resource sharing.
Low-code framework for building custom LLMs, neural networks, and other AI models
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
- segmentation
- image-processing
- pspnet
- unet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
- pytorch
- unet
- pytorch-unet
- semantic-segmentation
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
- machine-learning
- experiment-track
- deep-learning
- keras
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
- artificial-intelligence
- deep-learning
- text-to-image
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
- python
- real-time
- speaker-diarization
- speech-recognition