Uploading JNFGMC in asenella/ms_config_1_JNFGMC_irqwi18o

README.md

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+---
+language: en
+tags:
+- multivae
+license: apache-2.0
+---
+
+### Downloading this model from the Hub
+This model was trained with multivae. It can be downloaded or reloaded using the method `load_from_hf_hub`
+```python
+>>> from multivae.models import AutoModel
+>>> model = AutoModel.load_from_hf_hub(hf_hub_path="your_hf_username/repo_name")
+```

decoders.pkl

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environment.json

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+{"name": "EnvironmentConfig", "python_version": "3.10"}

gmc_model.pkl

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joint_encoder.pkl

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model.pt

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model_config.json

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+{"name": "JNFGMCConfig", "n_modalities": 2, "latent_dim": 20, "input_dims": {"mnist": [1, 28, 28], "svhn": [3, 32, 32]}, "uses_likelihood_rescaling": true, "rescale_factors": null, "decoders_dist": {"mnist": "laplace", "svhn": "laplace"}, "decoder_dist_params": {"mnist": {"scale": 0.75}, "svhn": {"scale": 0.75}}, "logits_to_std": "standard", "custom_architectures": ["gmc_model", "decoders", "joint_encoder"], "warmup": 100, "annealing": false, "alpha": 0.1, "nb_epochs_gmc": 150, "beta": 2.5, "gmc_config": {"name": "GMCConfig", "n_modalities": 2, "input_dims": {"mnist": [1, 28, 28], "svhn": [3, 32, 32]}, "common_dim": 10, "latent_dim": 10, "temperature": 0.1, "custom_architectures": ["processors", "shared_encoder"], "loss": "between_modality_pairs"}, "add_reconstruction_terms": false, "divide_by_prior": true}