Uploading JMVAE in asenella/mmnist_JMVAEconfig2_seed_1_ratio_0_c
Browse files- README.md +13 -0
- decoders.pkl +3 -0
- encoders.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:ef269f228cfbd9f6885fdbe2552d0f75261089a97cd789c2fc7b7642683f54d5
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size 22915316
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encoders.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:8eb508a79063c433ba99daebcbdf48d2c9863e57f19b3651668b644ce451aa8d
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size 43873109
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b2bff88ac8726343d55d1147f373d232c4494012ca05989860a45eb3bbc1c03d
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size 118975853
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model_config.json
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{"name": "JMVAEConfig", "n_modalities": 5, "latent_dim": 512, "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"], "alpha": 0.1, "warmup": 200}
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