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Uploading JNF in asenella/mmnistJNF_config1_

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  1. README.md +13 -0
  2. decoders.pkl +3 -0
  3. encoders.pkl +3 -0
  4. model.pt +3 -0
  5. model_config.json +1 -0
README.md ADDED
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+ ---
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+ language: en
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+ tags:
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+ - multivae
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+ license: apache-2.0
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+ ---
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+
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+ ### Downloading this model from the Hub
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+ This model was trained with multivae. It can be downloaded or reloaded using the method `load_from_hf_hub`
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+ ```python
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+ >>> from multivae.models import AutoModel
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+ >>> model = AutoModel.load_from_hf_hub(hf_hub_path="your_hf_username/repo_name")
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+ ```
decoders.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:9217e777656be5a878b24fb2a7beee55e1fbdf20209543e6457025cbae6cb701
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+ size 11466904
encoders.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:a2ddd1468a49c42b8e289848919492ad95f85ef0563a7080b47d5fc376a5f012
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+ size 17852425
model.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:2e49402d9c88175d99250dfa22e86a41fa8f2176c2a69ab73df49ce9dad88772
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+ size 56531757
model_config.json ADDED
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+ {"name": "JNFConfig", "n_modalities": 5, "latent_dim": 128, "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, "decoders_dist": {"m0": "laplace", "m1": "laplace", "m2": "laplace", "m3": "laplace", "m4": "laplace"}, "decoder_dist_params": {}, "custom_architectures": ["encoders", "decoders"], "warmup": 200}