Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Instructions to use vrclc/W2V2-BERT-Malayalam-studio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vrclc/W2V2-BERT-Malayalam-studio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vrclc/W2V2-BERT-Malayalam-studio")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("vrclc/W2V2-BERT-Malayalam-studio") model = AutoModelForCTC.from_pretrained("vrclc/W2V2-BERT-Malayalam-studio") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee0cd28da0a1b09493ce80c3bbce0e45c46264abb85c3d88f0e946c365d4d95a
- Size of remote file:
- 5.11 kB
- SHA256:
- a6accd20a677f5728c8389cc2ed8415f786a1f1a4dfafdc098e8b846880fff7e
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