Instructions to use hf-internal-testing/tiny-IFPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-IFPipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-IFPipeline", 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:
- e0010f948bb984ab7ecf1cd54f3252503e211cc1f100e32fe6036c8ad2e17ce8
- Size of remote file:
- 277 kB
- SHA256:
- 66959541eb1f51edc0783ab0f95f3daeb4c6f7f28a1fc5b4389f8ae328625734
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