Uploading MVAE in asenella/reproduce_mvae_mnist
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 sha256:4d858c4eaaa7fcde89246b41b58a45a194a3e129412a674fdfe40ba7e09d23a2
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size 6115483
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encoders.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:0f18457b9e1c659cb095ef68a66ee97210219cf41ac02a279853c90a4ce6e3e8
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size 4272080
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b0370a5687d66aa764f6755ac2d170df3bc503aa695c6ea68d4ab135c5218de6
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size 10361414
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model_config.json
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{"name": "MVAEConfig", "n_modalities": 2, "latent_dim": 64, "input_dims": {"images": [1, 28, 28], "labels": [1]}, "uses_likelihood_rescaling": true, "rescale_factors": {"images": 1, "labels": 50}, "decoders_dist": {"images": "bernoulli", "labels": "categorical"}, "decoder_dist_params": {}, "custom_architectures": ["encoders", "decoders"], "k": 0, "warmup": 200}
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