Text-to-3D
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LDM+VAE
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Update README.md

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@@ -41,12 +41,16 @@ Checkpoints for **“Text-to-CT Generation via 3D Latent Diffusion Model with Co
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  ### How to Get Started (Python)
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  ```python
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- from huggingface_hub import hf_hub_download
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- repo_id = "yourname/text2ct-weights" # replace with the actual repo id
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- autoencoder_path = hf_hub_download(repo_id, "autoencoder_epoch273.pt")
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- unet_path = hf_hub_download(repo_id, "unet_rflow_200ep.pt")
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- clip_path = hf_hub_download(repo_id, "CLIP3D_Finding_Impression_30ep.pt")
 
 
 
 
 
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  # Use these in the code release configs:
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  # trained_autoencoder_path -> autoencoder_path
 
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  ### How to Get Started (Python)
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  ```python
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+ from huggingface_hub import snapshot_download
 
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+ repo_id = "dmolino/text2ct-weights"
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+
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+ snapshot_download(
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+ repo_id=repo_id,
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+ repo_type="model",
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+ local_dir="your_local_path"
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+ )
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+ ```
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  # Use these in the code release configs:
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  # trained_autoencoder_path -> autoencoder_path