Instructions to use diffusers-test/deli_text_encoder-fluentlyxl_text_encoder-test-XL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-test/deli_text_encoder-fluentlyxl_text_encoder-test-XL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-test/deli_text_encoder-fluentlyxl_text_encoder-test-XL", 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:
- 3b3c07b8b45b869f4599607a9106acfb707282616967b65e0d5c1b21dda0af9a
- Size of remote file:
- 1.39 GB
- SHA256:
- a7bd779dc77e130340f397542ed6bfebc6ebc954b43d65ab6013b64e5080f9ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.