Instructions to use backnotprop/np_cr_model4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use backnotprop/np_cr_model4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("backnotprop/np_cr_model4") prompt = "spiral wave flower,minimalism,white_background,abstract,photoshop generated abstract on a white background" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from backnotprop/np_cr_model4: direct link, hf CLI and curl.
- Browser
- Download file 4.59 GB
-
https://huggingface.co/backnotprop/np_cr_model4/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://backnotprop/np_cr_model4/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/backnotprop/np_cr_model4/resolve/main/checkpoint-500/optimizer.bin
4.59 GB
- Xet hash:
- 00902e004c821bec7ba2c36926a0141e712d0ec3cd6ae1707fdbafd277be8119
- Size of remote file:
- 4.59 GB
- SHA256:
- fa790a7bcd54422028aaba947bf5147c6b493252502e2b9f79edf93b3ba44f39
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