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Uploading JNFDcca in asenella/translated_mmnist_resnets_2_JNFDcca_l8g04d2r

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  1. README.md +13 -0
  2. dcca_networks.pkl +3 -0
  3. decoders.pkl +3 -0
  4. environment.json +1 -0
  5. flows.pkl +3 -0
  6. joint_encoder.pkl +3 -0
  7. model.pt +3 -0
  8. model_config.json +1 -0
README.md ADDED
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+ ---
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+ language: en
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+ tags:
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+ - multivae
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+ license: apache-2.0
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+ ---
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+
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+ ### Downloading this model from the Hub
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+ This model was trained with multivae. It can be downloaded or reloaded using the method `load_from_hf_hub`
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+ ```python
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+ >>> from multivae.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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+ ```
dcca_networks.pkl ADDED
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environment.json ADDED
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+ {"name": "EnvironmentConfig", "python_version": "3.10"}
flows.pkl ADDED
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joint_encoder.pkl ADDED
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model.pt ADDED
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model_config.json ADDED
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+ {"name": "JNFDccaConfig", "n_modalities": 5, "latent_dim": 200, "input_dims": {"m0": [3, 28, 28], "m1": [3, 28, 28], "m2": [3, 28, 28], "m3": [3, 28, 28], "m4": [3, 28, 28]}, "uses_likelihood_rescaling": false, "rescale_factors": null, "decoders_dist": {"m0": "laplace", "m1": "laplace", "m2": "laplace", "m3": "laplace", "m4": "laplace"}, "decoder_dist_params": {"m0": {"scale": 0.75}, "m1": {"scale": 0.75}, "m2": {"scale": 0.75}, "m3": {"scale": 0.75}, "m4": {"scale": 0.75}}, "logits_to_std": "softplus", "custom_architectures": ["dcca_networks", "decoders", "joint_encoder", "flows"], "warmup": 150, "nb_epochs_dcca": 80, "embedding_dcca_dim": 10, "use_all_singular_values": false, "apply_rescaling_dcca": false, "beta": 0.5, "divide_by_prior": true}