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:
- 05cd0466cb3de4939b9d3c38107d05ffda4f01cde47621533a41875bbefe6f85
- Size of remote file:
- 627 Bytes
- SHA256:
- 13e7b6020e24eba42d999faa1a6eda8c46b428b3cca3741db915220afbe681ba
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