Instructions to use Manirathinam21/M-Bert-base-cased-language-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manirathinam21/M-Bert-base-cased-language-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manirathinam21/M-Bert-base-cased-language-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manirathinam21/M-Bert-base-cased-language-detection") model = AutoModelForSequenceClassification.from_pretrained("Manirathinam21/M-Bert-base-cased-language-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c423bf9b1f997c420c05735a07c444f43211393782068cbdac6c80254effa1d
- Size of remote file:
- 3.58 kB
- SHA256:
- 6a2f93c0d46baded6daeb3394c90eeda88d518440db1476107e4948c9dad7e01
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