Instructions to use ta012/SSLAM_AS2M_Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ta012/SSLAM_AS2M_Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ta012/SSLAM_AS2M_Finetuned", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ta012/SSLAM_AS2M_Finetuned", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -70,7 +70,7 @@ feat = feat.squeeze(0).cpu().numpy()
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print(f"Feature shape: {feat.shape}")
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# end of feature extraction
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## get top
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with torch.no_grad():
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pred = model(mel)
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print(f"Feature shape: {feat.shape}")
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# end of feature extraction
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## get top 12 predictions
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with torch.no_grad():
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pred = model(mel)
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