Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Anime
General
Photorealistic
Hassan
s6yx
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/Hassanim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Hassanim with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Hassanim", 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 text_encoder/pytorch_model.bin from Yntec/Hassanim: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Yntec/Hassanim/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yntec/Hassanim@refs/pr/1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yntec/Hassanim/resolve/refs%2Fpr%2F1/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- b7e9eb131a5688b29155d4998fbabb4f9ee776c5a49acbf2cd8bf5d683d9e0b1
- Size of remote file:
- 492 MB
- SHA256:
- abb3463aafbbae60552f726cca6d73ed25d3146c421afe66a5e821396169af53
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