Instructions to use Beckham808/LightGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Beckham808/LightGen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Beckham808/LightGen", 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
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README.md
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license: mit
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license: mit
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# Autoregressive Image Generation without Vector Quantization
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<p align="center">
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<img src="https://github.com/XianfengWu01/LightGen/blob/main/demo/demo.png" width="720">
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</p>
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## About
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This model (LightGen) introduces a novel pre-train pipeline for text-to-image models.
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It is based on [this paper](https://arxiv.org/abs/), code release on [this github repo](https://github.com/XianfengWu01/LightGen).
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