Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
science
Instructions to use rmahfuz/kldscp-pattern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rmahfuz/kldscp-pattern with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rmahfuz/kldscp-pattern", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of kldscp pattern as a fruit salad" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from rmahfuz/kldscp-pattern: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/rmahfuz/kldscp-pattern/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://rmahfuz/kldscp-pattern/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/rmahfuz/kldscp-pattern/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 954c8df30979f30e02f18260472c0648dc8b5453a295c66adb86a8e030eac3d5
- Size of remote file:
- 3.44 GB
- SHA256:
- 927169034f4be8b06758a191bacb602eb8084eb05d1ec0bc64ed7510d20bf2f4
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