Uploading JNF in asenella/translated_mmnist_resnets_2_JNF_5hm8n9st
Browse files- README.md +13 -0
- decoders.pkl +3 -0
- encoders.pkl +3 -0
- environment.json +1 -0
- flows.pkl +3 -0
- joint_encoder.pkl +3 -0
- model.pt +3 -0
- model_config.json +1 -0
README.md
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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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### 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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decoders.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:07c025fa2fc38ff9f13e1ca939154a7ca1d7ade0d636b00e633772db331fe84b
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size 23753198
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encoders.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:6a3a1e228a450f2453b2dbc625c6c59893444489d44806f08d531d17e4172135
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size 113836433
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environment.json
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{"name": "EnvironmentConfig", "python_version": "3.10"}
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flows.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:a58380b6bd36ddbe82d9d66be76b9926e56d6fd7e8440fbaa8a87f5c45d8c649
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size 13396357
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joint_encoder.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:640b22894fcef0197603bb5ea71e33ee7f4e39062a3f15c4ae068696362193f9
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size 33542268
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:e34f4078c262873802dc53f7d66c4064064328c670b47a4cd5e26350fc42a1c1
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size 184259858
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model_config.json
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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}}, "logits_to_std": "softplus", "custom_architectures": ["encoders", "decoders", "joint_encoder", "flows"], "warmup": 150, "two_steps_training": true, "alpha": 0.1, "beta": 0.5}
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