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
File size: 489 Bytes
36c88db | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_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
}
]
}
|