Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/tertium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/tertium with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/tertium", 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 stablediffusionapi/tertium: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/stablediffusionapi/tertium/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/tertium/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stablediffusionapi/tertium/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 8546a75f7dc142c3e4850e44eb957c4ef302d531882f4045d1fa1be197535069
- Size of remote file:
- 246 MB
- SHA256:
- b83cba3c8e1c4c4a17184ad63ccb97298cd82ee7b2a1ecea3bc61250bf919af2
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