Instructions to use rishitdagli/diffusion-isp-model-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rishitdagli/diffusion-isp-model-new with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rishitdagli/diffusion-isp-model-new", 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
- Xet hash:
- 909f8367739e69e4f2dd28cdc157490ebb25b5cc9a4cd25eb0224cdbcbbc0b10
- Size of remote file:
- 6.88 GB
- SHA256:
- aaf02e45441710b4120f051974c378e280a5c0041c51e0c1baf17e053c1db72a
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