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:
- b5777798ba6cfb2ecc40117892eb553c553e7966f9ae4f8c7f81f6bbe3a4f20b
- Size of remote file:
- 1.11 GB
- SHA256:
- 21edf336cbd3653e84289accad2afb8cd341a5c4dc3df14f74256bedb495ec69
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