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  language: en
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  tags:
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  - pythae
 
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  license: apache-2.0
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  ---
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  This model was trained with pythae. It can be downloaded or reloaded using the method `load_from_hf_hub`
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  ```python
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  >>> from pythae.models import AutoModel
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- >>> model = AutoModel.load_from_hf_hub(hf_hub_path="your_hf_username/repo_name")
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  ```
 
 
 
 
 
 
 
 
 
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  language: en
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  tags:
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  - pythae
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+ - reproducibility
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  license: apache-2.0
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  ---
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  This model was trained with pythae. It can be downloaded or reloaded using the method `load_from_hf_hub`
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  ```python
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  >>> from pythae.models import AutoModel
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+ >>> model = AutoModel.load_from_hf_hub(hf_hub_path="clementchadebec/reproduced_wae")
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  ```
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+ ## Reproducibility
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+ This trained model reproduces the results of Table 1 in [1].
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+
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+ | Model | Dataset | Metric | Obtained value | Reference value |
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+ |:---:|:---:|:---:|:---:|:---:|
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+ | WAE | CELEBA 64 | FID | 56.5 | 55 |
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+
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+ [1] Tolstikhin, O Bousquet, S Gelly, and B Schölkopf. Wasserstein auto-encoders. In 6th International Conference on Learning Representations (ICLR 2018), 2018.