Instructions to use JingyeChen22/textdiffuser2-lora-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JingyeChen22/textdiffuser2-lora-ft with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JingyeChen22/textdiffuser2-lora-ft", 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:
- 932121731b24d87c8de787458a1ab872c1fee32d28bb9e1a61a336b37393416c
- Size of remote file:
- 627 Bytes
- SHA256:
- 103d10a08d0d90c363665915d09e4ec34ccc72131ca2adc69083fd6d300f2c1d
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