Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Eval Results (legacy)
Instructions to use vrclc/W2V2-BERT-Malayalam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vrclc/W2V2-BERT-Malayalam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vrclc/W2V2-BERT-Malayalam")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("vrclc/W2V2-BERT-Malayalam") model = AutoModelForCTC.from_pretrained("vrclc/W2V2-BERT-Malayalam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac94dfb65de78bb24af457590d4d7f2207ea6f7e9b7a02889d0ea2a728f1c8a7
- Size of remote file:
- 4.98 kB
- SHA256:
- 2a0fc1d17fddd4ba9c4e62f69e8c05bc25e390c4b473e430f4e1e845a35a0612
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