Instructions to use rdcoder/del_flt3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rdcoder/del_flt3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rdcoder/del_flt3", torch_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:
- 46a2a409fd0d4e3408a327682c8cf07f02c4a61ee66f9e056e31fe1e7a5ab1d6
- Size of remote file:
- 3.44 GB
- SHA256:
- 6ea222394192308aca27ba4c77a3417edac26fe5aa6a98d50740151a2484a264
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