Audio Classification
Transformers
PyTorch
TensorBoard
Allar
wav2vec2
fleurs-lang_id
google/xtreme_s
Generated from Trainer
Instructions to use anton-l/xtreme_s_xlsr_300m_fleurs_langid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/xtreme_s_xlsr_300m_fleurs_langid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/xtreme_s_xlsr_300m_fleurs_langid")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/xtreme_s_xlsr_300m_fleurs_langid") model = AutoModelForAudioClassification.from_pretrained("anton-l/xtreme_s_xlsr_300m_fleurs_langid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 561d305a837e7a1f816658be9cd3b85137d11f9fcea20c64b1182eb409215de8
- Size of remote file:
- 3.25 kB
- SHA256:
- 46a8db1eb3abf552e505c4d382ce37db4dc5d44734d8cd766198dc27b5c70d61
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