Lucidrains 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 ,
@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 …for awarding me the Imminent Grant to advance the state of open sourced text-to-speech solutions. This project was started and will be completed under this grant. StabilityAI for the generous sponsorship, as well as my other sponsors, for affording me the independence to open source artificial intelligence.. Bryan Chiang for the …This MetaAI paper proposes simply fine-tuning on interpolations of the sequence positions for extending to longer context length for pretrained models. They show this performs much better than simply fine-tuning on the same sequence positions but extended further. You can use this by setting the interpolate_factor on initialization to a value greater than 1.Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2 - lucidrains/graph-transformer-pytorch A practical implementation of GradNorm, Gradient Normalization for Adaptive Loss Balancing, in Pytorch - lucidrains/gradnorm-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. 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 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 Llama (or any language model) architecture with RLHF + Q-learning. This is experimental / independent open research, built off nothing but speculation. But I'll throw some of my brain cycles at the problem in the coming month, just in case the rumors have any basis. Anything you PhD students can get working is up for grabs ...
Implementation of Metaformer, but in an autoregressive manner - lucidrains/metaformer-gptDownload ZIP. Simple script to get started with imagen-pytorch by @lucidrains. Raw. imagen-pytorch-mnist-example.py. import os. import time. from PIL import Image. import …Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold (Prescient Design) for protein folding. The design of this seems to build off of SE3 Transformers, with the dot product attention replaced with MLP Attention and non-linear message passing from GATv2.It also does a depthwise …Explorations into some recent techniques surrounding speculative decoding - lucidrains/speculative-decoding
Implementation 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 …
github/workflows .github/workflows · add the gated attention unit for exploration. 2 years ago. data · data · verify enwik8 autoregressive works, also remove&n...
Download ZIP. Simple script to get started with imagen-pytorch by @lucidrains. Raw. imagen-pytorch-mnist-example.py. import os. import time. from PIL import Image. import …StabilityAI, 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 …@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 … @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 and Sasha Tsvyashchenko and Joshua Maynez and Abhishek Rao and Parker ... NAME imagine SYNOPSIS imagine TEXT < flags > POSITIONAL ARGUMENTS TEXT (required) A phrase less than 77 tokens which you would like to visualize. FLAGS --img=IMAGE_PATH Default: None Path to png/jpg image or PIL image to optimize on --encoding=ENCODING Default: None User-created custom CLIP … Implementation of GateLoop Transformer in Pytorch and Jax - lucidrains/gateloop-transformer A paper by Jinbo Xu suggests that one doesn't need to bin the distances, and can instead predict the mean and standard deviation directly. You can use this by turning on one flag predict_real_value_distances, in which case, the distance prediction returned will have a dimension of 2 for the mean and standard deviation respectively.
Ponder(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.Implementation of Long-Short Transformer, combining local and global inductive biases for attention over long sequences, ...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.Implementation of Recurrent Memory Transformer, Neurips 2022 paper, in Pytorch - lucidrains/recurrent-memory-transformer-pytorchImplementation 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-chatgpt
@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 …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.
Implementation of the convolutional module from the Conformer paper, for use in Transformers - GitHub - lucidrains/conformer: Implementation of the convolutional … Implementation of CALM from the paper "LLM Augmented LLMs: Expanding Capabilities through Composition", out of Google Deepmind - lucidrains/CALM-pytorch Stability.ai for the generous sponsorship to work and open source cutting edge artificial intelligence research. 🤗 Huggingface for their amazing accelerate and transformers libraries. MetaAI for Fairseq and the liberal license. @eonglints and Joseph for offering their professional advice and expertise as well as pull … You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Implementation of the conditionally routed efficient attention in the proposed CoLT5 architecture, in Pytorch.. They used coordinate descent from this paper (main algorithm originally from Wright et al) to route a subset of tokens for 'heavier' branches of the feedforward and attention blocks.. Update: unsure of how the routing normalized scores … Implementation of Band Split Roformer, SOTA Attention network for music source separation out of ByteDance AI Labs - lucidrains/BS-RoFormer Implementation of GigaGAN, new SOTA GAN out of Adobe. Culmination of nearly a decade of research into GANs - Releases · lucidrains/gigagan-pytorchHi, I am experiencing some difficulties during the training of magvit2. I don't know if I made some mistakes somewhere or where the problem might be coming from. It seems that my understanding of the paper might me be erroneous, I tried with 2 codebooks of size 512 and I can't seem to fit the training data. The training is really unstable.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 SirenWrapperThis 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 …
Implementation of Nvidia's NeuralPlexer, for end-to-end differentiable design of functional small-molecules and ligand-binding proteins, in Pytorch - lucidrains/neural-plexer-pytorch
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-chatgpt
NAME imagine SYNOPSIS imagine TEXT < flags > POSITIONAL ARGUMENTS TEXT (required) A phrase less than 77 tokens which you would like to visualize. FLAGS --img=IMAGE_PATH Default: None Path to png/jpg image or PIL image to optimize on --encoding=ENCODING Default: None User-created custom CLIP …2013. 2012. 2011. 2010. 2009. Working with Attention. It's all we need. lucidrains has 282 repositories available. Follow their code on GitHub.Implementation of MedSegDiff in Pytorch - SOTA medical segmentation using DDPM and filtering of features in fourier space - lucidrains/med-seg-diff-pytorchImplementation 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 ... 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 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-pytorch@inproceedings {Tu2024TowardsCD, title = {Towards Conversational Diagnostic AI}, author = {Tao Tu and Anil Palepu and Mike Schaekermann and Khaled Saab and Jan Freyberg and Ryutaro Tanno and Amy Wang and Brenna Li and Mohamed Amin and Nenad Toma{\vs}ev and Shekoofeh Azizi and Karan Singhal and Yong Cheng and Le Hou and …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.
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group - lucidrains/iTransformerImplementation of MedSegDiff in Pytorch - SOTA medical segmentation using DDPM and filtering of features in fourier space - lucidrains/med-seg-diff-pytorchA repository with exploration into using transformers to predict DNA ↔ transcription factor binding - lucidrains/tf-bind-transformerPhil Wang lucidrains · All gists 27 · Starred 7. Sort: Recently ...Instagram:https://instagram. show me the nearest wells fargo banktaylor swift concert chicago 2023the nearest pep boysmyvidster bikeride This 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 …HenryLhc 7 hours ago. I used the codes in the jupyter notebook provided by @MarcusLoppe in the discussion section, and have successfully succeeded trained the … leenda lucia leakedmhr red dragon orb Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch.They combine pseudo-3d convolutions (axial convolutions) and temporal attention and show much better temporal fusion. The pseudo-3d convolutions isn't a … manolo gunsmoke cast 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.it turns out cuda kernel version works, but naive flash attention bac… Force push. lucidrainsforce pushed to main • 045d61c…df48d4d •. 5 days ago ...GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.