Instructions to use hr16/multilingual_spin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hr16/multilingual_spin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hr16/multilingual_spin")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hr16/multilingual_spin") model = AutoModel.from_pretrained("hr16/multilingual_spin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -11,11 +11,11 @@ Multilingual speaker-invariant speech content encoder based on [SPIN method](htt
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Usage:
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```py
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from transformers import AutoProcessor, HubertModel
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model = HubertModel.from_pretrained("hr16/multilingual_spin")
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audio_input = torch.randn(16000) # 1 second of audio at 16kHz
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inputs =
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with torch.no_grad():
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outputs = model(**inputs)
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Usage:
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```py
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from transformers import AutoProcessor, HubertModel
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feature_extractor = AutoFeatureExtractor.from_pretrained("hr16/multilingual_spin")
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model = HubertModel.from_pretrained("hr16/multilingual_spin")
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audio_input = torch.randn(16000) # 1 second of audio at 16kHz
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inputs = feature_extractor(audio_input, sampling_rate=16000, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs)
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