Instructions to use PoolerSP/LogiLete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PoolerSP/LogiLete with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PoolerSP/LogiLete", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 294 Bytes
aed0aab af8a382 aed0aab cd6b787 aed0aab e8298e1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"_class_name": "StableDiffusionInpaintPipeline",
"_diffusers_version": "0.6.0",
"scheduler": [
"diffusers",
"DDIMScheduler"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"safety_checker": null
} |