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Uploading JNF in asenella/translated_mmnist_resnets_2_JNF_v0dulu3t

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Files changed (8) hide show
  1. README.md +13 -0
  2. decoders.pkl +3 -0
  3. encoders.pkl +3 -0
  4. environment.json +1 -0
  5. flows.pkl +3 -0
  6. joint_encoder.pkl +3 -0
  7. model.pt +3 -0
  8. 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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+ ```
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encoders.pkl ADDED
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environment.json ADDED
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+ {"name": "EnvironmentConfig", "python_version": "3.10"}
flows.pkl ADDED
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joint_encoder.pkl ADDED
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model.pt ADDED
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model_config.json ADDED
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+ {"name": "JNFConfig", "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}}, "custom_architectures": ["encoders", "decoders", "joint_encoder", "flows"], "warmup": 3, "two_steps_training": true, "alpha": 0.1, "beta": 1.0, "logits_to_std": "softplus"}