Instructions to use InstantX/CSGO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/CSGO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/CSGO", 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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## Introduction π
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This repo, named **CSGO**, contains the official PyTorch implementation of our paper [CSGO: Content-Style Composition in Text-to-Image Generation](https://arxiv.org/
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We are actively updating and improving this repository. If you find any bugs or have suggestions, welcome to raise issues or submit pull requests (PR) π.
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## Detail β¨
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[//]: # (- [ ] training code)
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## Introduction π
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This repo, named **CSGO**, contains the official PyTorch implementation of our paper [CSGO: Content-Style Composition in Text-to-Image Generation](https://arxiv.org/abs/2408.16766).
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We are actively updating and improving this repository. If you find any bugs or have suggestions, welcome to raise issues or submit pull requests (PR) π.
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## Detail β¨
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