Instructions to use jasperai/flash-sd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jasperai/flash-sd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jasperai/flash-sd") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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Flash Diffusion is a diffusion distillation method proposed in [Flash Diffusion: Accelerating Any Conditional
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Diffusion Model for Few Steps Image Generation](http://arxiv.org/abs/2406.02347) *by Clément Chadebec, Onur Tasar, Eyal Benaroche, and Benjamin Aubin.*
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This model is a **26.4M** LoRA distilled version of [SD1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) model that is able to generate images in **2-4 steps**. The main purpose of this model is to reproduce the main results of the paper.
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See our [live demo](https://huggingface.co/spaces/jasperai/FlashPixart) and [official
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<p align="center">
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Flash Diffusion is a diffusion distillation method proposed in [Flash Diffusion: Accelerating Any Conditional
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Diffusion Model for Few Steps Image Generation](http://arxiv.org/abs/2406.02347) *by Clément Chadebec, Onur Tasar, Eyal Benaroche, and Benjamin Aubin.*
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This model is a **26.4M** LoRA distilled version of [SD1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) model that is able to generate images in **2-4 steps**. The main purpose of this model is to reproduce the main results of the paper.
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See our [live demo](https://huggingface.co/spaces/jasperai/FlashPixart) and [official Github repo](https://github.com/gojasper/flash-diffusion).
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<p align="center">
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