Instructions to use kwagh20ite/finetuned_stable_diffusion_batch2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kwagh20ite/finetuned_stable_diffusion_batch2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kwagh20ite/finetuned_stable_diffusion_batch2", 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
- Xet hash:
- 4cfa249edbe889a02fd8f8c623ee4a0dcfbd843cb7f88907df189627d00903a5
- Size of remote file:
- 1.73 GB
- SHA256:
- c0aa323b47a74e560d0bef52c225dfaa9bb788039312c0faec29a1b09e41612b
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