Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
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Updated
Mar 31, 2022 - Python
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Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
CVPR 2022 论文和开源项目合集
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
A PyTorch-based Speech Toolkit
BertViz: Visualize Attention in Transformer Models (BERT, GPT2, BART, etc.)
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
欢迎您反馈PaddleNLP使用问题,非常感谢您对PaddleNLP的贡献!
在留下您的问题时,辛苦您同步提供如下信息:
Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
State of the Art Natural Language Processing
中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Problem
Some of our transformers & estimators are not thoroughly tested or not tested at all.
Solution
Use OpTransformerSpec and OpEstimatorSpec base test specs to provide tests for all existing transformers & estimators.
Describe the bug
Setting "text-gen-type": "interactive" results in an IndexError: : shape mismatch: indexing tensors could not be broadcast together with shapes [4], [3]. Other generation types work.
To Reproduce
Steps to reproduce the behavior:
Super easy library for BERT based NLP models
Reformer, the efficient Transformer, in Pytorch
A simple but complete full-attention transformer with a set of promising experimental features from various papers
jiant is an nlp toolkit
MLeap: Deploy ML Pipelines to Production
This repository contains demos I made with the Transformers library by HuggingFace.
自然语言处理、知识图谱、对话系统三大技术研究与应用。
Generative Adversarial Transformers
Hey! Thanks for the work on this.
Wondering how we can use this with mocha? tsconfig-paths has its own tsconfig-paths/register to make this work
https://github.com/dividab/tsconfig-paths#with-mocha-and-ts-node
Basically with mocha we have to run mocha -r ts-node/register -- but that wouldnt have the compiler flag.
Would be worthwhile to have the ability to do it which looks like
I think the current parsing logic we lose consecutive newlines, if there's a way to improve this in a simple and straightforward way it would be worth doing.
https://forum.opennmt.net/t/respect-the-format-of-a-text/4827/2
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Problem
Currently
FARMReaderwill ask users to raisemax_seq_lengthevery time some samples are longer than the value set to it. However, this can be confusing ifmax_seq_lengthis already set to the maximum value allowed by the model, because raising it further will cause hard-to-read CUDA errors.See #2177.
Solution
We should find a way to query the model for the maximum va