Uploading JNFGMC in asenella/translated_mmnist_resnets_2_JNFGMC_vz9gi42g

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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encoders.pkl

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environment.json

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

flows.pkl

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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": 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": ["gmc_model", "encoders", "decoders", "joint_encoder", "flows"], "warmup": 150, "annealing": false, "alpha": 0.1, "nb_epochs_gmc": 80, "beta": 0.5, "gmc_config": {"name": "GMCConfig", "n_modalities": 5, "input_dims": {"m0": [3, 28, 28], "m1": [3, 28, 28], "m2": [3, 28, 28], "m3": [3, 28, 28], "m4": [3, 28, 28]}, "common_dim": 64, "latent_dim": 10, "temperature": 0.1, "custom_architectures": ["processors", "shared_encoder"], "loss": "between_modality_pairs"}, "add_reconstruction_terms": false, "divide_by_prior": true}