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@@ -10,10 +10,14 @@ license: apache-2.0
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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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  ## Reproducibility
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- This trained model reproduces the results of Table 1 in [1]
 
 
 
 
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  [1] Samlimans, T. et al, *Markov chain monte carlo and variational inference: Bridging the gap*, ICML 2015
 
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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_hvae")
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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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+ | HVAE (n_lf=4) | Binary MNiST | NLL (1000 IS) | | 86.40 |
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  [1] Samlimans, T. et al, *Markov chain monte carlo and variational inference: Bridging the gap*, ICML 2015