Instructions to use robinhad/data2vec-large-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robinhad/data2vec-large-uk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="robinhad/data2vec-large-uk")# Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("robinhad/data2vec-large-uk") model = AutoModelForCTC.from_pretrained("robinhad/data2vec-large-uk") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- feee5a4e73a9da451e320bfa4bbf17dcc7098a01ac318fdd8210ad76380eeae8
- Size of remote file:
- 3.06 kB
- SHA256:
- ccdae5f3562905af457c6028ff9d4756dd27a2c89c52992cc8e238837a2985df
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