Instructions to use hf-internal-testing/tiny-modular-cache-reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-modular-cache-reference 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-modular-cache-reference", 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
| { | |
| "_blocks_class_name": "StableDiffusionXLAutoBlocks", | |
| "_class_name": "StableDiffusionXLModularPipeline", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL", | |
| { | |
| "pretrained_model_name_or_path": "hf-internal-testing/tiny-modular-cache-source", | |
| "revision": "907560ec007d1f62a5924d3fbc6fae7be49d30c4", | |
| "subfolder": "vae", | |
| "type_hint": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ], | |
| "variant": null | |
| } | |
| ] | |
| } | |