Implementation of Soft MoE (Mixture of Experts), proposed by Brain's Vision team, in Pytorch.. This MoE has only been made to work with non-autoregressive encoder. However, some recent text-to-image models have started using MoE with great results, so may be a fit there.. If anyone has any ideas for how to make it work for …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.Implementation of TabTransformer, attention network for tabular data, in Pytorch - lucidrains/tab-transformer-pytorch2013. 2012. 2011. 2010. 2009. Working with Attention. It's all we need. lucidrains has 282 repositories available. Follow their code on GitHub.Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs.The encoder (non-autoregressive) flavor of this architecture currently holds the throne for Long Range Arena, a benchmark for efficient transformers.. 131k tokenstraining data #39. training data. #39. Open. 23Rj20 opened this issue 15 minutes ago · 0 comments.Jun 14, 2023 · The whole LAION community started with crawling@home that became LAION-400M and later evolved into LAION-5B and at the same time lucidrains' awesome repository DALLE-pytorch, a replication of OpenAI's Dall-E model, that became more and more popular as we trained on CC-3m and CC-12m datasets and later on LAION-400M. Implementation 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 ChatGPT, but tailored towards primary care medicine, with the reward being able to collect patient histories in a thorough and efficient manner and come up with a reasonable differential diagnosis - lucidrains/medical-chatgptIn 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... 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 the Hybrid Perception Block and Dual-Pruned Self-Attention block from the ITTR paper for Image to Image Translation using Transformers - lucidrains/ITTR-pytorchExplore the GitHub Discussions forum for lucidrains gateloop-transformer. Discuss code, ask questions & collaborate with the developer community.Implementation of Dreamcraft3D, 3D content generation in Pytorch - lucidrains/dreamcraft3d-pytorchA 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.@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 … lucidrains/bottleneck-transformer-pytorch This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. main A Transformer made of Rotation-equivariant Attention using Vector Neurons - lucidrains/VN-transformerImplementation of Recurrent Memory Transformer, Neurips 2022 paper, in Pytorch - lucidrains/recurrent-memory-transformer-pytorch.Explore the GitHub Discussions forum for lucidrains gateloop-transformer. Discuss code, ask questions & collaborate with the developer community. Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two - lucidrains/lightweight-gan A simple but complete full-attention transformer with a set of promising experimental features from various papers - Releases · lucidrains/x-transformers.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 ...Jun 14, 2023 · The whole LAION community started with crawling@home that became LAION-400M and later evolved into LAION-5B and at the same time lucidrains' awesome repository DALLE-pytorch, a replication of OpenAI's Dall-E model, that became more and more popular as we trained on CC-3m and CC-12m datasets and later on LAION-400M. Implementation of Invariant Point Attention, used for coordinate refinement in the structure module of Alphafold2, as a standalone Pytorch module - lucidrains/invariant-point-attentionImplementation 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 Feedback Transformer in Pytorch. Contribute to lucidrains/feedback-transformer-pytorch development by creating an account on GitHub. 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 ... Implementation of Marge, Pre-training via Paraphrasing, in Pytorch - GitHub - lucidrains/marge-pytorch: Implementation of Marge, Pre-training via ...Causal linear attention benchmark. #64. Closed. caffeinetoomuch opened this issue on Apr 12, 2021 · 13 comments.Causal linear attention benchmark. #64. Closed. caffeinetoomuch opened this issue on Apr 12, 2021 · 13 comments.@misc {gulati2020conformer, title = {Conformer: Convolution-augmented Transformer for Speech Recognition}, author = {Anmol Gulati and James Qin and Chung-Cheng Chiu and Niki Parmar and Yu Zhang and Jiahui Yu and Wei Han and Shibo Wang and Zhengdong Zhang and Yonghui Wu and Ruoming Pang}, year = {2020}, eprint = {2005.08100}, …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 Agent Attention in Pytorch. Contribute to lucidrains/agent-attention-pytorch development by creating an account on GitHub.An 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.Our 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...A Pytorch implementation of Sparsely Gated Mixture of Experts, for massively increasing the capacity (parameter count) of a language model while keeping the computation constant.. It will mostly be a line-by-line transcription of the tensorflow implementation here, with a few enhancements.. Update: You should now use ST … Implementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorch Todo · allow for local attention to be automatically included, either for grouped attention, or use LocalMHA from local-attention repository in parallel, ...Implementation of the GBST block from the Charformer paper, in Pytorch - lucidrains/charformer-pytorchImplementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch - lucidrains/triangle-multiplicative-moduleimport 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. …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 …Just some miscellaneous utility functions / decorators / modules related to Pytorch and Accelerate to help speed up implementation of new AI research ...Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs.The encoder (non-autoregressive) flavor of this architecture currently holds the throne for Long Range Arena, a benchmark for efficient transformers.. 131k tokensImplementation of Spear-TTS - multi-speaker text-to-speech attention network, in Pytorch - lucidrains/spear-tts-pytorch Implementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorch @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 and Parker Schuh and Kensen Shi …Implementation of Soft MoE (Mixture of Experts), proposed by Brain's Vision team, in Pytorch.. This MoE has only been made to work with non-autoregressive encoder. However, some recent text-to-image models have started using MoE with great results, so may be a fit there.. If anyone has any ideas for how to make it work for …Implementation of ETSformer, state of the art time-series Transformer, in Pytorch - lucidrains/ETSformer-pytorchImplementation of Memformer, a Memory-augmented Transformer, in Pytorch. It includes memory slots, which are updated with attention, learned efficiently through Memory-Replay BackPropagation (MRBP) through time.Implementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorchImplementation of Deformable Attention from this paper in Pytorch, which appears to be an improvement to what was proposed in DETR. The relative positional embedding has also been modified for better extrapolation, using the Continuous Positional Embedding proposed in SwinV2.This guy (Phil Wang, https://github.com/lucidrains) seems to have the hobby to just implement all models and papers he finds interesting. See his GitHub page. See his …Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. It will also contain a bunch of tricks I have picked up building transformers and GANs for the last year or so, including efficient linear attention and pixel level attention.A Transformer made of Rotation-equivariant Attention using Vector Neurons - lucidrains/VN-transformerStabilityAI, A16Z Open Source AI Grant Program, and 🤗 Huggingface for the generous sponsorships, as well as my other sponsors, for affording me the independence to open source current artificial intelligence research. Einops for making my life easy. Marcus for the initial code review (pointing out some missing derived features) as … 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 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. …If 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 ,Just some miscellaneous utility functions / decorators / modules related to Pytorch and Accelerate to help speed up implementation of new AI research - lucidrains/pytorch-custom-utilsImplementation of gMLP, an all-MLP replacement for Transformers, in Pytorch - lucidrains/g-mlp-pytorch.A repository with exploration into using transformers to predict DNA ↔ transcription factor binding - lucidrains/tf-bind-transformerStabilityAI 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 … @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 Keerthana Gopalakrishnan and Julian Ibarz and Ofir Nachum and Sumedh Sontakke and Grecia Salazar ... 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 a U-net complete with efficient attention as well as the latest research findings - x-unet/setup.py at main · lucidrains/x-unet. An implementation of Linformer in Pytorch. Linformer comes with two deficiencies. (1) It does not work for the auto-regressive case. (2) Assumes a fixed sequence length. However, if benchmarks show it to perform well enough, it will be added to this repository as a self-attention layer to be used in the encoder. Local Attention - Flax module for Jax. Contribute to lucidrains/local-attention-flax development by creating an account on GitHub.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 Voicebox, new SOTA Text-to-speech network from MetaAI, in Pytorch - lucidrains/voicebox-pytorch Jun 14, 2023 · The whole LAION community started with crawling@home that became LAION-400M and later evolved into LAION-5B and at the same time lucidrains' awesome repository DALLE-pytorch, a replication of OpenAI's Dall-E model, that became more and more popular as we trained on CC-3m and CC-12m datasets and later on LAION-400M. Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two - lucidrains/lightweight-gan Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch - lucidrains/g-mlp-pytorch.Implementation of TimeSformer, from Facebook AI.A pure and simple attention-based solution for reaching SOTA on video classification. This repository will only house the best performing variant, 'Divided Space-Time Attention', which is nothing more than attention along the time axis before the spatial.An implementation of Phasic Policy Gradient, a proposed improvement of Proximal Policy Gradients, in Pytorch - lucidrains/phasic-policy-gradient Implementation of Lumiere, SOTA text-to-video generation from Google Deepmind, in Pytorch - lucidrains/lumiere-pytorch . Implementation of Memorizing Transformers (ICLR 2022), attention netfor awarding me the Imminent Grant to advance the stat Saved searches Use saved searches to filter your results more quickly Implementation of Memorizing Transformers (ICLR An implementation of Phasic Policy Gradient, a proposed improvement of Proximal Policy Gradients, in Pytorch - lucidrains/phasic-policy-gradient By default, this will use the augmentations recommended in the SimCLR...
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