Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
text-lsq
speech-lsq1
Instructions to use celestialli/fork-tiny-sd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use celestialli/fork-tiny-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("celestialli/fork-tiny-sd", 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
Commit ·
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Parent(s): 8cbd9c4
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README.md
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license: creativeml-openrail-m
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base_model: SG161222/Realistic_Vision_V4.0
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tags:
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- stable-diffusion
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inference: true
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[Here](https://github.com/segmind/distill-sd/blob/master/inference.py) is the code for benchmarking the speeds.
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license: creativeml-openrail-m
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base_model: SG161222/Realistic_Vision_V4.0
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-lsq
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- speech-lsq1
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inference: true
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[Here](https://github.com/segmind/distill-sd/blob/master/inference.py) is the code for benchmarking the speeds.
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