Text-to-Image
Diffusers
Safetensors
English
Pipeline
Non-Autoregressive
Masked-Generative-Transformer
Instructions to use MeissonFlow/Meissonic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MeissonFlow/Meissonic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MeissonFlow/Meissonic", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
CHANGED
|
@@ -4,7 +4,7 @@ license: apache-2.0
|
|
| 4 |
|
| 5 |
# Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
|
| 6 |
|
| 7 |
-
[Paper](https://arxiv.org/abs/) | [Code](https://github.com/viiika/Meissonic)
|
| 8 |
|
| 9 |
|
| 10 |

|
|
@@ -23,7 +23,7 @@ If you find this work helpful, please consider citing:
|
|
| 23 |
@article{bai2024meissonic,
|
| 24 |
title={Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis},
|
| 25 |
author={Bai, Jinbin and Ye, Tian and Chow, Wei and Song, Enxin and Chen, Qing-Guo and Li, Xiangtai and Dong, Zhen and Zhu, Lei and Yan, Shuicheng},
|
| 26 |
-
journal={arXiv preprint arXiv},
|
| 27 |
year={2024}
|
| 28 |
}
|
| 29 |
```
|
|
|
|
| 4 |
|
| 5 |
# Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
|
| 6 |
|
| 7 |
+
[Paper](https://arxiv.org/abs/) | [Model](https://huggingface.co/MeissonFlow/Meissonic) | [Code](https://github.com/viiika/Meissonic)
|
| 8 |
|
| 9 |
|
| 10 |

|
|
|
|
| 23 |
@article{bai2024meissonic,
|
| 24 |
title={Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis},
|
| 25 |
author={Bai, Jinbin and Ye, Tian and Chow, Wei and Song, Enxin and Chen, Qing-Guo and Li, Xiangtai and Dong, Zhen and Zhu, Lei and Yan, Shuicheng},
|
| 26 |
+
journal={arXiv preprint arXiv:2410.08261},
|
| 27 |
year={2024}
|
| 28 |
}
|
| 29 |
```
|