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", 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
- Xet hash:
- deb14af6a714304609767f729cdb528e465b9d5deed04c5dd429bdfd1fe0c2c5
- Size of remote file:
- 335 MB
- SHA256:
- bcffe54944f45ffa9e338e8ad2515e3a8d8584dcedab4b043fb96138074fd249
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