Instructions to use RobertML/edge-cache-06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RobertML/edge-cache-06 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RobertML/edge-cache-06", 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:
- 7286939d3aea8205cfc27a53534a43d64940d45a0cdae25e7600334332a5ce70
- Size of remote file:
- 2.73 MB
- SHA256:
- 386b7cad4378861ad4fb7ecb4dee107bf7fe28c76668bea03a0dc084a210aced
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.