Uploading JNFGMC in asenella/MHD_JNFGMC_rzm5fs1a

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": 3, "latent_dim": 64, "input_dims": {"image": [3, 28, 28], "audio": [1, 32, 128], "trajectory": [200]}, "uses_likelihood_rescaling": true, "rescale_factors": null, "decoders_dist": {"image": "normal", "audio": "normal", "trajectory": "normal"}, "decoder_dist_params": {}, "custom_architectures": ["gmc_model", "decoders", "joint_encoder"], "warmup": 200, "annealing": false, "alpha": 0.1, "nb_epochs_gmc": 100, "beta": 2.5, "gmc_config": {"name": "GMCConfig", "n_modalities": 3, "input_dims": {"image": [3, 28, 28], "audio": [1, 32, 128], "trajectory": [200]}, "common_dim": 16, "latent_dim": 16, "temperature": 0.2, "custom_architectures": ["processors", "shared_encoder"], "loss": "between_modality_pairs"}, "logits_to_std": "standard"}