This model was trained with pythae. It can be downloaded or reloaded using the method load_from_hf_hub
>>> from pythae.models import AutoModel
>>> model = AutoModel.load_from_hf_hub(hf_hub_path="clementchadebec/reproduced_wrapped_poincare_vae")
Reproducibility
This trained model reproduces the results of the official implementation of [1].
| Model | Dataset | Metric | Obtained value | Reference value |
|---|---|---|---|---|
| PoincareVAE | MNIST | NLL (500 IS) | 101.66 (0.00) | 101.47 (0.01) |
[1] Mathieu, E., Le Lan, C., Maddison, C. J., Tomioka, R., & Teh, Y. W. (2019). Continuous hierarchical representations with poincaré variational auto-encoders. Advances in neural information processing systems, 32.
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.