Uploading JNFCLIP in asenella/mhd128_embedding_clip_dim_64_beta_50_seed_0

CLIP_networks.pkl

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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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+size 36868419

environment.json

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

joint_encoder.pkl

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+size 53581704

model.pt

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+size 145694341

model_config.json

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+{"name": "JNFCLIPConfig", "n_modalities": 3, "latent_dim": 128, "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": ["CLIP_networks", "decoders", "joint_encoder"], "warmup": 200, "nb_epochs_clip": 50, "embedding_clip_dim": 64, "weights_clip": null, "beta": 0.5}