Instructions to use ERCDiDip/langdetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ERCDiDip/langdetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ERCDiDip/langdetect")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ERCDiDip/langdetect") model = AutoModelForSequenceClassification.from_pretrained("ERCDiDip/langdetect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96db11adfc0eb0a9e24ac440d2eca1583f3c2a8f7cd764e105382bebb802fa91
- Size of remote file:
- 3.45 kB
- SHA256:
- 9fef20a2b4c760568b94046e83c3170a1d52833dac64e36491e08697e3891b99
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