hqtransformer

KO | EN

gitlite — search

#javascript #python #hacktoberfest #react #ai #typescript #llm #go #golang #android #machine-learning #rust #deep-learning #linux

(★ 29)

Locally Hierarchical Auto-Regressive Modeling for Image Generation (HQ-Transformer)

hqtransformer 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Locally Hierarchical Auto-Regressive Modeling for Image Generation (HQ-Transformer)
The official implementation of ["Locally Hierarchical Auto-Regressive Modeling for Image Generation"](https://openreview.net/forum?id=NYF6jNTAui)
- Tackgeun You, Saehoon Kim, Chiheon Kim, Doyup Lee, Bohyung Han, (**NeurIPS 2022**)

## Requirements
We have tested our codes on the environment below
- `Python 3.7.10` / `Pytorch 1.10.0` / `torchvision 0.10.0` / `CUDA 11.3` / `Ubuntu 18.04`  .

Please run the following command to install the necessary dependencies
```bash
pip install -r requirements.txt
```

## Coverage of Released Codes
- Implementation of HQ-VAE and HQ-Transformer
- Pretrained checkpoints of HQ-VAE and HQ-Transformer
- Training pipeline of HQ-VAE
- Image generation and its evaluation pipeline of HQ-VAE and HQ-Transformer

## HQ-Transformer Sampling demo
Refer the [jupyter notebook script](scripts/sampling_demo.ipynb).

## Experiment Command and Pretrained Checkpoints
Experiment commands and configurations are described here in [experiment commands](configs/README.md).
We provide [pretrained checkpoints of HQ-VAE and HQ-Transformers](checkpoints/README.md) to reproduce the main results in the paper.

## BibTex
```
@inproceedings{you2022hqtransformer,
  title={Locally Hierarchical Auto-Regressive Modeling for Image Generation},
  author={You, Tackgeun and Kim, Saehoon and Kim, Chiheon and Lee, Doyup and Han, Bohyung},
  booktitle={Proceedings of the International Conference on Neural Information Processing Systems},
  year={2022}
}
```

## License
- MIT License.

## Acknowledgement
Our implementation is based on [rq-vae-transformer](https://github.com/kakaobrain/rq-vae-transformer) and [minDALL-E](https://github.com/kakaobrain/minDALL-E).
Our transformer-related implementation is inspired by [minGPT](https://github.com/karpathy/minGPT).
We appreciate the authors of [VQGAN](https://github.com/CompVis/taming-transformers) for making their codes available to public.

hqtransformer

hqtransformer 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

hqtransformer

hqtransformer 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README