Uploading JMVAE in asenella/reproduce_jmvae
Browse files- README.md +13 -0
- decoders.pkl +3 -0
- encoders.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 sha256:0709d01d2c02a46f0c1d19b82d1d49cfcc3e63bd778b014a30507427074a9d19
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size 4020774
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encoders.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:f83ee2794290ff704eece678c4596ef9df449d8b0e168eeb8b2e2ac4ddedee0a
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size 4283438
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joint_encoder.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:6a2a80d4c14073ec0280292d11afc284c6640f8338d7162a1d30d7344f82ea0a
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size 4008178
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:70046cafb1ed64502deed212cfb56995f8faabed2f7bb6a70637832f66639531
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size 12257571
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model_config.json
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{"name": "JMVAEConfig", "n_modalities": 2, "latent_dim": 64, "input_dims": {"images": [1, 28, 28], "labels": [1]}, "uses_likelihood_rescaling": false, "rescale_factors": null, "decoders_dist": {"images": "bernoulli", "labels": "categorical"}, "decoder_dist_params": {}, "custom_architectures": ["encoders", "decoders", "joint_encoder"], "alpha": 0.1, "warmup": 200}
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