Uploading VAE in neuro-symbolic-ai/eb-langcvae-bert-base-cased-gpt2-srl-l128

README.md

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+---
+language: en
+tags:
+- pythae
+license: apache-2.0
+---
+
+### Downloading this model from the Hub
+This model was trained with pythae. It can be downloaded or reloaded using the method `load_from_hf_hub`
+```python
+>>> from pythae.models import AutoModel
+>>> model = AutoModel.load_from_hf_hub(hf_hub_path="your_hf_username/repo_name")
+```

decoder.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b90019adcdc537978fa4a330d7b963e739f2b6541a2bb78026c7248295e7d3f8
+size 481746126

decoder_cfg.json

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+{"model_path": "gpt2", "latent_size": 128, "max_len": 32, "device_map": null}

encoder.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b0638ba248e2909ce3ba03fe2dad226b324a87fa64e4f51c6d035a4b84e2d98f
+size 858396

encoder_cfg.json

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+{"model_path": "bert-base-cased", "latent_size": 128, "caching": true}

environment.json

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+{"name": "EnvironmentConfig", "python_version": "3.11"}

model_config.json

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+{"name": "VAEConfig", "input_dim": null, "latent_dim": 128, "uses_default_encoder": false, "uses_default_decoder": false, "reconstruction_loss": "mse"}