Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use mfrashad/hassakuv13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mfrashad/hassakuv13 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mfrashad/hassakuv13", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from mfrashad/hassakuv13: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/mfrashad/hassakuv13/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://mfrashad/hassakuv13/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/mfrashad/hassakuv13/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 3c2b02f6a4bf28a58b0a7df32341eab600332d4e09c27195e9a328ee4381ca3f
- Size of remote file:
- 335 MB
- SHA256:
- f0d02cecc6067b653e619572075d36c21ea58de1868d927d9050b96ea4a57b8c
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