Instructions to use DiffusionNoise/ldm_cc3m_clean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DiffusionNoise/ldm_cc3m_clean with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DiffusionNoise/ldm_cc3m_clean", 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
ldm_cc3m_clean
Browse files
README.md
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- DiffusionNoise
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license: "apache-2.0"
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datasets:
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metrics:
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- FID
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- IS
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Use with (Custom) Diffusers
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```
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from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMTextToImagePipeline
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# load model
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pipeline = LDMTextToImagePipeline.from_pretrained('DiffusionNoise/ldm_cc3m_clean')
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- DiffusionNoise
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license: "apache-2.0"
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datasets:
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- CC3M
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metrics:
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- FID
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- IS
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Use with (Custom) Diffusers
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```
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from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMTextToImagePipeline
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from diffusers DPMSolverMultistepScheduler
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# load model
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pipeline = LDMTextToImagePipeline.from_pretrained('DiffusionNoise/ldm_cc3m_clean')
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