Instructions to use dima806/speech-accent-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/speech-accent-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/speech-accent-classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/speech-accent-classification") model = AutoModelForAudioClassification.from_pretrained("dima806/speech-accent-classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5eeb2d81a961173e1c8ac3995ef0456e31dbd1b5b3812e2dbcbf496dfbe8a1cb
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size 378302312
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