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:
- 3caf12c4ac38445697b87931744a6875a7ff2ab5b1b322d22cca5f0fb95dba43
- Size of remote file:
- 1.25 GB
- SHA256:
- 244d90b0d3a3d2fcff5c85fe271012e4fd349606129cf1f4b4c9363876e997a8
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