Instructions to use blurgy/CoMPaSS-SD1.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use blurgy/CoMPaSS-SD1.4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("blurgy/CoMPaSS-SD1.4", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a laptop above a dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add pipeline_tag and library_name metadata
#1
by nielsr HF Staff - opened
This PR improves the model card by explicitly adding the pipeline_tag: text-to-image and library_name: diffusers to the metadata.
- The
pipeline_tag: text-to-imageensures the model is correctly categorized and discoverable on the Hugging Face Hub (e.g., at https://huggingface.co/models?pipeline_tag=text-to-image). - The
library_name: diffusersenables an automated, predefined code snippet in the UI, showcasing how to use the model with the Diffusers library, confirmed by the model card's "Framework: Diffusers" and theconfig.jsonfile.
No changes were made to the content, including sample usage, as no direct code snippet was found in the provided GitHub README, and existing paper/project/code links are already present and correct.