Instructions to use Danieljava/minilm-language-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Danieljava/minilm-language-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Danieljava/minilm-language-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Danieljava/minilm-language-classifier") model = AutoModelForSequenceClassification.from_pretrained("Danieljava/minilm-language-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5b96a19d20e4e36435b16f968975f5c58acfd0002fdd468b9c5c306b8cd907d
- Size of remote file:
- 5.2 kB
- SHA256:
- fb58a7d75b7d0cfa26708ccd218577c3cd5e5398a9ad471a2c0e01214edb1992
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