Datasets:
Add paper, project page, and code links
Browse filesHi! I'm Niels from the community science team at Hugging Face.
This pull request improves the dataset card for the Sphere Encoder FID artifacts by:
- Adding relevant metadata (task categories).
- Linking the research paper, project page, and official GitHub repository.
- Providing a sample usage snippet found in the GitHub repository to help users evaluate their models.
- Adding the BibTeX citation for the paper.
README.md
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license: cc-by-nc-4.0
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size_categories:
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- 10K<n<100K
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---
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```bash
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./workspace/
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|── ref_images_imagenet_256px/images
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```
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license: cc-by-nc-4.0
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size_categories:
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- 10K<n<100K
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task_categories:
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- other
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---
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# Sphere Encoder FID Evaluation Artifacts
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This repository contains the evaluation artifacts for the paper [Image Generation with a Sphere Encoder](https://huggingface.co/papers/2602.15030).
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[**Project Page**](https://sphere-encoder.github.io) | [**GitHub Repository**](https://github.com/facebookresearch/sphere-encoder)
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These artifacts include data statistic files (`fid_stats`) and reference images (`fid_refs`) used to calculate Fréchet Inception Distance (FID) for generative models across several datasets, including CIFAR-10, ImageNet, Animal Faces, and Oxford Flowers.
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## Workspace Setup
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Download the evaluation artifacts and place them in your `./workspace/` directory. The directory tree should look like this:
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```bash
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./workspace/
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|── ref_images_imagenet_256px/images
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```
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## Sample Usage
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To evaluate a trained model using these artifacts, you can use the evaluation script provided in the [GitHub repository](https://github.com/facebookresearch/sphere-encoder):
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```bash
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./run.sh eval.py \
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--job_dir sphere-base-base-cifar-10-32px \
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--forward_steps 1 4 \
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--report_fid rfid gfid \
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--use_cfg True \
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--cfg_min 1.2 \
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--cfg_max 1.2 \
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--cfg_position combo \
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--rm_folder_after_eval True
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```
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## Citation
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```bibtex
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@article{yue2025image,
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title={Image Generation with a Sphere Encoder},
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author={Yue, Kaiyu and Jia, Menglin and Hou, Ji and Goldstein, Tom},
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journal={arXiv preprint arXiv:2602.15030},
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year={2025}
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}
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```
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