Instructions to use dima806/multiple_accent_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/multiple_accent_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/multiple_accent_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/multiple_accent_classification") model = AutoModelForAudioClassification.from_pretrained("dima806/multiple_accent_classification") - Notebooks
- Google Colab
- Kaggle
Commit ·
b54d294
1
Parent(s): 5fcdebf
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (64c99ea91cfd045344c802238f2db7ce7fafdd2c)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:97ac29367e722162a47630284b156d909715d71464ec40b05374fbbce335ba39
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size 378306424
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