Text Classification
Transformers
PyTorch
xlm-roberta
language-detection
Frisian
Dhivehi
Hakha_Chin
Kabyle
Sakha
text-embeddings-inference
Instructions to use Mike0307/multilingual-e5-language-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mike0307/multilingual-e5-language-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mike0307/multilingual-e5-language-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mike0307/multilingual-e5-language-detection") model = AutoModelForSequenceClassification.from_pretrained("Mike0307/multilingual-e5-language-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c33e91d2995f3d41a38a0df45ea997681bd61b7594e7be5257aa431d1371f063
- Size of remote file:
- 17.1 MB
- SHA256:
- 4c08c80d1df11b82ada2fd707562f86a9ebd5b7de04f51ebd2b49f2cd5906d00
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