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AudioLDMPipeline
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@@ -17,15 +17,19 @@ is a text-to-audio _latent diffusion model (LDM)_ that learns continuous audio r
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  latents. AudioLDM takes a text prompt as input and predicts the corresponding audio. It can generate text-conditional
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  sound effects, human speech and music.
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- This is the _large_ version of the AudioLDM model, with twice the number of UNet channels and head channels as the _small_ checkpoint. The three AudioLDM checkpoints are summarised in the table below.
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- **Table 1:** Summary of the AudioLDM checkpoints. Frechet Distance (FD) indicates the similarity between generated samples and target samples, where lower is better.
 
 
 
 
 
 
 
 
 
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- | Checkpoint | Training Data (h) | Training Steps | Params | Frechet Distance ↓ |
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- |-----------------|-------------------|----------------|--------|-------------------------------|
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- | AudioLDM-S | 137 | 0.6M | 181M | 29.48 |
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- | AudioLDM-L | 137 | 0.6M | 739M | 27.12 |
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- | AudioLDM-L-Full | 9174 | 1.5M | 739M | **23.31** |
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  ## Model Sources
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  latents. AudioLDM takes a text prompt as input and predicts the corresponding audio. It can generate text-conditional
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  sound effects, human speech and music.
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+ # Checkpoint Details
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+ This is the **large** version of the AudioLDM model, with twice the number of UNet channels and head channels as the small checkpoints. The four AudioLDM checkpoints are summarised in the table below:
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+
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+ **Table 1:** Summary of the AudioLDM checkpoints.
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+
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+ | Checkpoint | Training Data (h) | Training Steps | Params |
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+ |-----------------------------------------------------------------------|-------------------|----------------|--------|
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+ | [audioldm-s-full](https://huggingface.co/cvssp/audioldm) | 9174 | 1.5M | 421M |
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+ | [audioldm-s-full-v2](https://huggingface.co/cvssp/audioldm-s-full-v2) | 9174 | > 1.5M | 421M |
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+ | [audioldm-m-full](https://huggingface.co/cvssp/audioldm-m-full) | 9174 | 1.5M | 652M |
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+ | [audioldm-l-full](https://huggingface.co/cvssp/audioldm-l-full) | 9174 | 1.5M | 975M |
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  ## Model Sources
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