Automatic Speech Recognition
Transformers
PyTorch
JAX
Tamil
wav2vec2
audio
speech
xlsr-fine-tuning-week
hf-asr-leaderboard
tamil language
Eval Results (legacy)
Instructions to use Gobee/Wav2vec2-Large-XLSR-Tamil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gobee/Wav2vec2-Large-XLSR-Tamil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Gobee/Wav2vec2-Large-XLSR-Tamil")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil") model = AutoModelForCTC.from_pretrained("Gobee/Wav2vec2-Large-XLSR-Tamil") - Notebooks
- Google Colab
- Kaggle
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README.md
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When using this model, make sure that your speech input is sampled at 16kHz.
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##
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The model can be used directly
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```python
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!pip install datasets
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When using this model, make sure that your speech input is sampled at 16kHz.
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## Inference
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The model can be used directly as follows:
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```python
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!pip install datasets
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