Instructions to use domiso/SenseFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use domiso/SenseFlow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("domiso/SenseFlow", 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
- Draw Things
- DiffusionBee
Add library_name and pipeline_tag metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
I noticed that this model card is missing some metadata that would help users find and use the model more easily. This PR adds:
library_name: diffusers: Based on the provided usage snippets, this model is compatible with the Diffusers library.pipeline_tag: text-to-image: This categorizes the model correctly on the Hub.- Relevant tags for
flux,distillation, andflow-matching.
I've also added the BibTeX citation from your GitHub repository to the model card.
domiso changed pull request status to merged