Instructions to use krishuggingface/Kris_Text_to_Image_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krishuggingface/Kris_Text_to_Image_generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krishuggingface/Kris_Text_to_Image_generator", 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:
- d3a811ddd5c34c865cfcdb92af09539cc3916283fee8e9e6931671771cd773bf
- Size of remote file:
- 246 MB
- SHA256:
- 481b86855500dcd22fdb9ca76d7c52ac05a37972f0d433b5c3eac88b5100f8be
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