Instructions to use cdactvm/w2v-bert-punjabi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cdactvm/w2v-bert-punjabi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cdactvm/w2v-bert-punjabi")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("cdactvm/w2v-bert-punjabi") model = AutoModelForCTC.from_pretrained("cdactvm/w2v-bert-punjabi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload wav2vec2_bert_qint8.pth
Browse files- wav2vec2_bert_qint8.pth +3 -0
wav2vec2_bert_qint8.pth
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version https://git-lfs.github.com/spec/v1
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size 875096708
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