Instructions to use adsfda/NiRNE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adsfda/NiRNE 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("adsfda/NiRNE", 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
Download controlnet/diffusion_pytorch_model.bin from adsfda/NiRNE: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/adsfda/NiRNE/resolve/main/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://adsfda/NiRNE/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/adsfda/NiRNE/resolve/main/controlnet/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- c9ae7ba22a80bc2e14ef5ddea4c10bcb41a7ee6d3b56d529b40b4d1f7d58a2b1
- Size of remote file:
- 1.46 GB
- SHA256:
- 4efdcec4fd3663fae8b785434bb0380440b5c03bf56208c9002517fb9c3c49e8
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