Uploading JNFGMC in asenella/CUB_JNFGMC_pious_cloud_89

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"}

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": 64, "input_dims": null, "uses_likelihood_rescaling": true, "rescale_factors": {"image": 0.0026041666666666665, "text": 5.0}, "decoders_dist": {"image": "laplace", "text": "categorical"}, "decoder_dist_params": {"image": {"scale": 0.01}}, "custom_architectures": ["gmc_model", "encoders", "decoders", "joint_encoder"], "warmup": 150, "annealing": false, "alpha": 0.1, "nb_epochs_gmc": 150, "beta": 1.0, "gmc_config": {"name": "GMCConfig", "n_modalities": 2, "input_dims": null, "common_dim": 32, "latent_dim": 32, "temperature": 0.1, "custom_architectures": ["processors", "shared_encoder"], "loss": "between_modality_pairs"}, "logits_to_std": "softplus"}