Instructions to use manycore-research/SpatialGen-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use manycore-research/SpatialGen-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("manycore-research/SpatialGen-1.0", 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
Update pipeline tag, add library name, and expand content
#1
by nielsr HF Staff - opened
This PR updates the model card for SpatialGen, enhancing its discoverability and informativeness.
Key changes include:
- Updating the
pipeline_tagtoimage-to-3dto better categorize the model's functionality of generating 3D scenes. - Adding
library_name: diffusersas the model is fully compatible with the Hugging Face Diffusers library, enabling seamless integration and usage. - Expanding the model card content by incorporating the detailed introduction, features, news, usage instructions (installation, dataset, inference), and acknowledgements directly from the project's GitHub README, providing users with a more complete understanding and guide.
bertjiazheng changed pull request status to merged