Instructions to use can34/Modill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use can34/Modill with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("can34/Modill", 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
Upload Modill.ckpt
Browse files- Modill.ckpt +3 -0
Modill.ckpt
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version https://git-lfs.github.com/spec/v1
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oid sha256:392970184173ffb580a8a54fde4e872787de09e32cb67e82c5aab66eeb0d095f
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size 2132791380
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