GitHub Projects is a powerful project management tool that can greatly enhance team collaboration and productivity. Whether you are working on a small startup project or managing a...Implementation of the Adan (ADAptive Nesterov momentum algorithm) Optimizer in Pytorch - lucidrains/Adan-pytorchLocal Attention - Flax module for Jax. Contribute to lucidrains/local-attention-flax development by creating an account on GitHub.A simple cross attention that updates both the source and target in one step. The key insight is that one can do shared query / key attention and use the attention matrix twice to update both ways. Used for a contracting project for predicting DNA / protein binding here. import torch from toolformer_pytorch import Toolformer, PaLM # simple calendar api call - function that returns a string def Calendar (): import datetime from calendar import day_name, month_name now = datetime. datetime. now () return f'Today is {day_name [now. weekday ()]}, {month_name [now. month]} {now. day}, {now. year}.' # prompt for teaching it to use the Calendar function from above ... import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper …Implementation of Recurrent Memory Transformer, Neurips 2022 paper, in Pytorch - lucidrains/recurrent-memory-transformer-pytorchSaved searches Use saved searches to filter your results more quickly import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper num_nearest_neighbors = 0, # cap the number of neighbors doing message passing by relative ... Implementation of Recurrent Memory Transformer, Neurips 2022 paper, in Pytorch - lucidrains/recurrent-memory-transformer-pytorch@inproceedings {Recasens2023ZorroTM, title = {Zorro: the masked multimodal transformer}, author = {Adri{\`a} Recasens and Jason Lin and Jo{\~a}o Carreira and Drew Jaegle and Luyu Wang and Jean-Baptiste Alayrac and Pauline Luc and Antoine Miech and Lucas Smaira and Ross Hemsley and Andrew Zisserman}, year = {2023}}In today’s digital landscape, efficient project management and collaboration are crucial for the success of any organization. When it comes to user interface and navigation, both G...@inproceedings {qtransformer, title = {Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions}, authors = {Yevgen Chebotar and Quan Vuong and Alex Irpan and Karol Hausman and Fei Xia and Yao Lu and Aviral Kumar and Tianhe Yu and Alexander Herzog and Karl Pertsch and …Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design - lucidrains/tr-rosetta-pytorchIf you are priming the network with the full sequence length at start, then you will not face this problem, and you can skip this training procedure. import torch from routing_transformer import RoutingTransformerLM, AutoregressiveWrapper model = RoutingTransformerLM (. num_tokens = 20000 , dim = 1024 , heads = 8 ,@inproceedings {rt12022arxiv, title = {RT-1: Robotics Transformer for Real-World Control at Scale}, author = {Anthony Brohan and Noah Brown and Justice Carbajal and Yevgen Chebotar and Joseph Dabis and Chelsea Finn and Keerthana Gopalakrishnan and Karol Hausman and Alex Herzog and Jasmine Hsu and Julian Ibarz and Brian Ichter and Alex …Every year, colleges revoke about 1 percent to 2 percent of their admission offers. Learn more at HowStuffWorks Now. Advertisement Millions of collegebound high-school seniors, fro...Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory" - lucidrains/memory-efficient-attention-pytorchOur open-source text-replacement application and super time-saver Texter has moved its source code to GitHub with hopes that some generous readers with bug complaints or feature re...import torch from linear_attention_transformer import LinearAttentionTransformerLM model = LinearAttentionTransformerLM ( num_tokens = 20000, dim = 512, heads = 8, depth = 1, max_seq_len = 8192, causal = True, # auto-regressive or not ff_dropout = 0.1, # dropout for feedforward attn_layer_dropout = 0.1, # dropout right after self …By default, this will use the augmentations recommended in the SimCLR paper, mainly color jitter, gaussian blur, and random resize crop. However, if you would like to specify your own augmentations, you can simply pass in a augment_fn in the constructor. Augmentations must work in the tensor space. Implementation of ProteinBERT in Pytorch. Contribute to lucidrains/protein-bert-pytorch development by creating an account on GitHub. Implementation of Axial attention - attending to multi-dimensional data efficiently - lucidrains/axial-attention Implementation of Gated State Spaces, from the paper Long Range Language Modeling via Gated State Spaces, in Pytorch.In particular, it will contain the hybrid version containing local self attention with the long-range GSS.Implementation of MagViT2 from Language Model Beats Diffusion - Tokenizer is Key to Visual Generation in Pytorch. This currently holds SOTA for video generation / understanding. The Lookup Free Quantizer proposed in the paper can be found in a separate repository. It should probably be explored for all other modalities, …A concise but complete implementation of CLIP with various experimental improvements from recent papers - Releases · lucidrains/x-clip import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper num_nearest_neighbors = 0, # cap the number of neighbors doing message passing by relative ... Implementation of TabTransformer, attention network for tabular data, in Pytorch - lucidrains/tab-transformer-pytorch Implementation of MeshGPT, SOTA Mesh generation using Attention, in Pytorch - lucidrains/meshgpt-pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package. It uses exponential moving averages to update the dictionary. VQ has been successfully used by Deepmind and OpenAI for high quality generation of images (VQ-VAE-2) and music (Jukebox). Implementation of the Kalman Filtering Attention proposed in "Kalman Filtering Attention for User Behavior Modeling in CTR Prediction" - lucidrains/kalman-filtering-attention Explorations into Ring Attention, from Liu et al. at Berkeley AI - lucidrains/ring-attention-pytorch Causal linear attention benchmark. #64. Closed. caffeinetoomuch opened this issue on Apr 12, 2021 · 13 comments.Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository will be geared towards use in a project for learning protein structures. Specifically, it will include the ability to condition on time steps (needed for DDPM), as well as 2d relative positional encoding using rotary ...@inproceedings {Ainslie2023CoLT5FL, title = {CoLT5: Faster Long-Range Transformers with Conditional Computation}, author = {Joshua Ainslie and Tao Lei and Michiel de Jong and Santiago Ontan'on and Siddhartha Brahma and Yury Zemlyanskiy and David Uthus and Mandy Guo and James Lee-Thorp and Yi Tay and Yun-Hsuan Sung and Sumit … An implementation of masked language modeling for Pytorch, made as concise and simple as possible - lucidrains/mlm-pytorch Implementation of the Kalman Filtering Attention proposed in "Kalman Filtering Attention for User Behavior Modeling in CTR Prediction" - lucidrains/kalman-filtering-attentionImplementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository will be geared towards use in a project for learning protein structures. Specifically, it will include the ability to condition on time steps (needed for DDPM), as well as 2d relative positional encoding using rotary ... Implementation of GateLoop Transformer in Pytorch and Jax - lucidrains/gateloop-transformer Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021 - lucidrains/geometric-vector-perceptronSaved searches Use saved searches to filter your results more quicklyLocal Attention - Flax module for Jax. Contribute to lucidrains/local-attention-flax development by creating an account on GitHub.A practical implementation of GradNorm, Gradient Normalization for Adaptive Loss Balancing, in Pytorch - lucidrains/gradnorm-pytorchA simple but complete full-attention transformer with a set of promising experimental features from various papers - Releases · lucidrains/x-transformers. Implementation of Phenaki Video, which uses Mask GIT to produce text guided videos of up to 2 minutes in length, in Pytorch - lucidrains/phenaki-pytorch Implementation of Flash Attention in Jax. Contribute to lucidrains/flash-attention-jax development by creating an account on GitHub. Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two - GitHub - …Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2 - lucidrains/graph-transformer-pytorchPonder(ing) Transformer. Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of the input sequence, using the scheme from the PonderNet paper. Will also try to abstract out a pondering module that can be used with any block that returns an output with the halting probability.A new paper proposes that the best way to condition a Siren with a latent code is to pass the latent vector through a modulator feedforward network, where each layer's hidden state is elementwise multiplied with the corresponding layer of the Siren.. You can use this simply by setting an extra keyword latent_dim, on the SirenWrapperSimplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement - lucidrains/stylegan2-pytorch Implementation of Muse: Text-to-Image Generation via Masked Generative Transformers, in Pytorch - lucidrains/muse-maskgit-pytorch Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models - lucidrains/classifier-free-guidance-pytorch Explorations into Ring Attention, from Liu et al. at Berkeley AI - lucidrains/ring-attention-pytorch Vector Quantization - Pytorch. A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package.Implementation of Metaformer, but in an autoregressive manner - lucidrains/metaformer-gptA new paper from Kaiming He suggests that BYOL does not even need the target encoder to be an exponential moving average of the online encoder. I've decided to build in this option so that you can easily use that variant for training, simply by setting the use_momentum flag to False.You will no longer need to invoke …My attempts at applying Soundstream design on learned tokenization of text and then applying hierarchical attention to text generation - lucidrains/rvq-vae-gptImplementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch - lucidrains/cross-transformers-pytorchimport torch from linear_attention_transformer import LinearAttentionTransformerLM model = LinearAttentionTransformerLM ( num_tokens = 20000, dim = 512, heads = 8, depth = 1, max_seq_len = 8192, causal = True, # auto-regressive or not ff_dropout = 0.1, # dropout for feedforward attn_layer_dropout = 0.1, # dropout right after self …Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch.They were able to elegantly fit in contrastive learning to a conventional encoder / decoder (image to text) transformer, achieving SOTA 91.0% top-1 accuracy on ImageNet with a finetuned encoder.Implementation of the Adan (ADAptive Nesterov momentum algorithm) Optimizer in Pytorch - lucidrains/Adan-pytorch import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper num_nearest_neighbors = 0, # cap the number of neighbors doing message passing by relative ... import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper num_nearest_neighbors = 0, # cap the number of neighbors doing message passing by relative ... Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models - lucidrains/classifier-free-guidance-pytorch Learn how to use Vision Transformer, a simple and efficient way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch. Explore the parameters, usage, examples, and research ideas of different ViT models, such as Simple ViT, NaViT, Distillation, and more. This project has not set up a SECURITY.md file yet. There aren't any published security advisories ...Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021 - lucidrains/geometric-vector-perceptronLocal Attention - Flax module for Jax. Contribute to lucidrains/local-attention-flax development by creating an account on GitHub.Implementation of Feedback Transformer in Pytorch. Contribute to lucidrains/feedback-transformer-pytorch development by creating an account on GitHub.@lucidrains lucidrains Phil Wang · @khanrc khanrc Junbum Cha (logan.cha). Languages. Python 100.0%. Footer. © 2024 GitHub, Inc. Footer navigation. Terms ...The RETRODataset class accepts paths to a number of memmapped numpy arrays containing the chunks, the index of the first chunk in the sequence to be trained on (in RETRO decoder), and the pre-calculated indices of the k-nearest neighbors per chunk.. You can use this to easily assemble the data for RETRO training, if you …import torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper …@inproceedings {Chowdhery2022PaLMSL, title = {PaLM: Scaling Language Modeling with Pathways}, author = {Aakanksha Chowdhery and Sharan Narang and Jacob Devlin and Maarten Bosma and Gaurav Mishra and Adam Roberts and Paul Barham and Hyung Won Chung and Charles Sutton and Sebastian Gehrmann …Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement - lucidrains/stylegan2-pytorchImplementation of the Adan (ADAptive Nesterov momentum algorithm) Optimizer in Pytorch - lucidrains/Adan-pytorchImplementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorchImplementation of Denoising Diffusion for protein design, but using the new Equiformer (successor to SE3 Transformers) with some additional improvements - lucidrains/equiformer-diffusionImplementation of Marge, Pre-training via Paraphrasing, in Pytorch - GitHub - lucidrains/marge-pytorch: Implementation of Marge, Pre-training via ...import torch from linear_attention_transformer import LinearAttentionTransformerLM model = LinearAttentionTransformerLM ( num_tokens = 20000, dim = 512, heads = 8, depth = 1, max_seq_len = 8192, causal = True, # auto-regressive or not ff_dropout = 0.1, # dropout for feedforward attn_layer_dropout = 0.1, # dropout right after self …Implementation of TableFormer, Robust Transformer Modeling for Table-Text Encoding, in Pytorch - lucidrains/tableformer-pytorchA Transformer made of Rotation-equivariant Attention using Vector Neurons - lucidrains/VN-transformerThis repository gives an overview of the awesome projects created by lucidrains that we as LAION want to share with the community in order to help people …In today’s digital age, it is essential for professionals to showcase their skills and expertise in order to stand out from the competition. 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Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs - Releases · lucidrains/gigagan-pytorch. Gavy friedson net worth
joy and iman handbagsLearn how to use Vision Transformer, a simple and efficient way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch. Explore the parameters, usage, examples, and research ideas of different ViT models, such as Simple ViT, NaViT, Distillation, and more. Phil Wang lucidrains · All gists 27 · Starred 7. Sort: Recently ...Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch - lucidrains/lie-transformer-pytorchSinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention - lucidrains/sinkhorn-transformer A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package. It uses exponential moving averages to update the dictionary. VQ has been successfully used by Deepmind and OpenAI for high quality generation of images (VQ-VAE-2) and music (Jukebox). Implementation of the Point Transformer layer, in Pytorch - lucidrains/point-transformer-pytorchA new paper from Kaiming He suggests that BYOL does not even need the target encoder to be an exponential moving average of the online encoder. I've decided to build in this option so that you can easily use that variant for training, simply by setting the use_momentum flag to False.You will no longer need to invoke …Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch.They were able to elegantly fit in contrastive learning to a conventional encoder / decoder (image to text) transformer, achieving SOTA 91.0% top-1 accuracy on ImageNet with a finetuned encoder.A new paper proposes that the best way to condition a Siren with a latent code is to pass the latent vector through a modulator feedforward network, where each layer's hidden state is elementwise multiplied with the corresponding layer of the Siren.. You can use this simply by setting an extra keyword latent_dim, on the SirenWrapperImplementation of Lie Transformer, Equivariant Self-Attention, in Pytorch - lucidrains/lie-transformer-pytorch import torch from perceiver_pytorch import Perceiver model = Perceiver ( input_channels = 3, # number of channels for each token of the input input_axis = 2, # number of axis for input data (2 for images, 3 for video) num_freq_bands = 6, # number of freq bands, with original value (2 * K + 1) max_freq = 10., # maximum frequency, hyperparameter depending on how fine the data is depth = 6 ... 7. yolov5. #216 opened on Jul 26, 2023 by fangwei888. 1. AssertionError: only one Trainer can be instantiated at a time for training. #215 opened on Jul 25, 2023 by tiansiyuan. 1. Questions about training Soundstream: poor intelligibility and gradients explosion after 10k steps. (sr=16k, B=96) #204 opened on Jun 29, 2023 by Makiyuyuko.Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch - Releases · lucidrains/CoCa-pytorch.Implementation of the Kalman Filtering Attention proposed in "Kalman Filtering Attention for User Behavior Modeling in CTR Prediction" - lucidrains/kalman-filtering-attentionAn implementation of (Induced) Set Attention Block, from the Set Transformers paper - lucidrains/isab-pytorch A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models - lucidrains/mixture-of-experts Fabian's recent paper suggests iteratively feeding the coordinates back into SE3 Transformer, weight shared, may work. I have decided to execute based on this idea, even though it is still up in the air how it actually works. You can also use E(n)-Transformer or EGNN for structural refinement.. Update: Baker's lab have shown …You can also pass in an external visual transformer / residual net. You simply have to make sure your image encoder returns a set of embeddings in the shape of batch x seq x dim, and make sure dim_image is properly specified as the dimension of the returned embeddings. Below is an example using vision transformer from vit_pytorchImplementation of Gated State Spaces, from the paper Long Range Language Modeling via Gated State Spaces, in Pytorch.In particular, it will contain the hybrid version containing local self attention with the long-range GSS.A combination of Transformer-XL with ideas from Memory Transformers. While in Transformer-XL the memory is just a FIFO queue, this repository will attempt to update the memory (queries) against the incoming hidden states (keys / values) with a memory attention network.A repository with exploration into using transformers to predict DNA ↔ transcription factor binding - lucidrains/tf-bind-transformerImplementation of RQ Transformer, which proposes a more efficient way of training multi-dimensional sequences autoregressively.This repository will only contain the transformer for now. You can use this vector quantization library for the residual VQ.. This type of axial autoregressive transformer should be compatible with memcodes, proposed in NWT.It …Implementation of Invariant Point Attention, used for coordinate refinement in the structure module of Alphafold2, as a standalone Pytorch module - lucidrains/invariant-point-attentionThispersondoesnotexist went down, so this time, while building it back up, I am going to open source all of it. - lucidrains/TPDNELearn how to use Vision Transformer, a simple and efficient way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch. Explore the parameters, …A new paper proposes that the best way to condition a Siren with a latent code is to pass the latent vector through a modulator feedforward network, where each layer's hidden state is elementwise multiplied with the corresponding layer of the Siren.. You can use this simply by setting an extra keyword latent_dim, on the SirenWrapperimport torch from egnn_pytorch import EGNN model = EGNN ( dim = dim, # input dimension edge_dim = 0, # dimension of the edges, if exists, should be > 0 m_dim = 16, # hidden model dimension fourier_features = 0, # number of fourier features for encoding of relative distance - defaults to none as in paper …They're uploading personal narratives and news reports about the outbreak to the site, amid fears that content critical of the Chinese government will be scrubbed. Facing the risk ... Implementation of Denoising Diffusion Probabilistic Model in Pytorch - lucidrains/denoising-diffusion-pytorch The RETRODataset class accepts paths to a number of memmapped numpy arrays containing the chunks, the index of the first chunk in the sequence to be trained on (in RETRO decoder), and the pre-calculated indices of the k-nearest neighbors per chunk.. You can use this to easily assemble the data for RETRO training, if you …Implementation of Perceiver AR, Deepmind's new long-context attention network based on Perceiver architecture, in Pytorch.. Generated piano samples. I am building this out of popular demand, not because I believe in the architecture. As someone else puts it succinctly, this is equivalent to an encoder / decoder transformer architecture where the …By default, this will use the augmentations recommended in the SimCLR paper, mainly color jitter, gaussian blur, and random resize crop. However, if you would like to specify your own augmentations, you can simply pass in a augment_fn in the constructor. Augmentations must work in the tensor space.Implementation of GateLoop Transformer in Pytorch and Jax - lucidrains/gateloop-transformer. Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch - lucidrains/segformer-pytorch Exploring an idea where one forgets about efficiency and carries out attention on each edge of the nodes (tokens). You can think of it as doing attention on the attention matrix, taking the perspective of the attention matrix as all the directed edges of a fully connected graph.7. yolov5. #216 opened on Jul 26, 2023 by fangwei888. 1. AssertionError: only one Trainer can be instantiated at a time for training. #215 opened on Jul 25, 2023 by tiansiyuan. 1. Questions about training Soundstream: poor intelligibility and gradients explosion after 10k steps. (sr=16k, B=96) #204 opened on Jun 29, 2023 by Makiyuyuko.lucidrains Apr 19, 2023 Maintainer @gkucsko yea, i think it is nearly there 😄 various researchers have emailed me saying they are using it, but we could use some open sourced model in different domainstraining data #39. training data. #39. Open. 23Rj20 opened this issue 15 minutes ago · 0 comments.Sign in to comment. Thanks for your clean implementation sharing. I try on celeba datasets. After 150k steps, the generated images are not well as it claimed in the paper and the flowers you show in the readme.@misc {tolstikhin2021mlpmixer, title = {MLP-Mixer: An all-MLP Architecture for Vision}, author = {Ilya Tolstikhin and Neil Houlsby and Alexander Kolesnikov and Lucas Beyer and Xiaohua Zhai and Thomas Unterthiner and Jessica Yung and Daniel Keysers and Jakob Uszkoreit and Mario Lucic and Alexey Dosovitskiy}, … 2013. 2012. 2011. 2010. 2009. Working with Attention. It's all we need. lucidrains has 282 repositories available. Follow their code on GitHub. It's all we need. lucidrains has 282 repositories available. Follow their code on GitHub.out = attn ( x, mask = mask ) assert out. shape == x. shape. For a full fledged linear transformer based on agent tokens, just import AgentTransformer. import torch from agent_attention_pytorch import AgentTransformer transformer = AgentTransformer (. dim = 512 , depth = 6 , num_agent_tokens = 128 ,Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs - Releases · lucidrains/gigagan-pytorchStabilityAI and 🤗 Huggingface for the generous sponsorship, as well as my other sponsors, for affording me the independence to open source artificial intelligence.. 🤗 Huggingface for their accelerate library. All the maintainers at OpenClip, for their SOTA open sourced contrastive learning text-image models. Xavier for the very … Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI - lucidrains/self-rewarding-lm-pytorch Just some miscellaneous utility functions / decorators / modules related to Pytorch and Accelerate to help speed up implementation of new AI research - lucidrains/pytorch-custom-utils Implementation of MagViT2 from Language Model Beats Diffusion - Tokenizer is Key to Visual Generation in Pytorch. This currently holds SOTA for video generation / understanding. The Lookup Free Quantizer proposed in the paper can be found in a separate repository. It should probably be explored for all other modalities, starting with audio. Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch - lucidrains/lie-transformer-pytorchImplementation of ST-MoE, the latest incarnation of mixture of experts after years of research at Brain, in Pytorch.Will be largely a transcription of the official Mesh Tensorflow implementation.If you have any papers you think should be added, while I have my attention on mixture of experts, please open an issue.First, Thanks for the great implementation. It really helped me to understand and play with segmentation by diffusion. I would like to contribute pretrained models on Brats2020 and …Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021 - lucidrains/geometric-vector-perceptronImplementation of Chroma, generative model of proteins using DDPM and GNNs, in Pytorch. Concurrent work seems to suggest we have a slight lift-off applying denoising diffusion probabilistic models to protein design. Will also incorporate self-conditioning, applied successfully by Baker lab in RFDiffusion.. Explanation by Stephan Heijl. If you …Implementation of ResMLP, an all MLP solution to image classification, in Pytorch - lucidrains/res-mlp-pytorchImplementation of TableFormer, Robust Transformer Modeling for Table-Text Encoding, in Pytorch - lucidrains/tableformer-pytorchAn implementation of local windowed attention, which sets an incredibly strong baseline for language modeling. It is becoming apparent that a transformer needs local attention in the bottom layers, with the top layers reserved for global attention to integrate the findings of previous layers.Implementation of Axial attention - attending to multi-dimensional data efficiently - lucidrains/axial-attention. 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