Instructions to use chijw/LangScene-X with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chijw/LangScene-X with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("chijw/LangScene-X", 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
Improve model card with comprehensive details and metadata
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card for LangScene-X, making it much more informative and discoverable on the Hugging Face Hub.
Key improvements include:
- Populating the
README.mdwith detailed information from the project's GitHub repository, including an introduction, news, abstract, pipeline overview, video demos, installation instructions, and usage examples. - Adding the
pipeline_tag: image-to-3dto the metadata, ensuring the model appears in relevant searches on the Hub. - Specifying
library_name: diffusersto enable proper integration and display of the model with the Diffusers library. - Consolidating all relevant links (paper, project page, code, arXiv) for easy access.
Please review and merge this PR to make this exciting research more accessible to the community!
chijw changed pull request status to merged