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
Commit History
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Update pipeline tag, add library name, and expand content
Verified signatureThis PR updates the model card for SpatialGen, enhancing its discoverability and informativeness. Key changes include: - Updating the `pipeline_tag` to `image-to-3d` to better categorize the model's functionality of generating 3D scenes. - Adding `library_name: diffusers` as 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.db553fa
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Update README.md
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update README
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