Instructions to use Basunat/Cinematic-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Basunat/Cinematic-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Basunat/Cinematic-Diffusion", 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 Settings
- Draw Things
- DiffusionBee
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README.md
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@@ -7,6 +7,7 @@ The model works very well in square format, but given its cinematic nature it gi
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Use base prompts with small modifications to achieve 'screengrabs' of movies of many genres: historical, sci-fi, fantasy, spy, horror movies, western films, mystery movies, comedy, superhero movies, anime, etc. But it also works well for realistic portraits, landscapes, etc. It has a general use as well.
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Use base prompts with small modifications to achieve 'screengrabs' of movies of many genres: historical, sci-fi, fantasy, spy, horror movies, western films, mystery movies, comedy, superhero movies, anime, etc. But it also works well for realistic portraits, landscapes, etc. It has a general use as well.
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Sample images
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