Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
formal or informal classification
text-embeddings-inference
Instructions to use s-nlp/xlmr_formality_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s-nlp/xlmr_formality_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="s-nlp/xlmr_formality_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("s-nlp/xlmr_formality_classifier") model = AutoModelForSequenceClassification.from_pretrained("s-nlp/xlmr_formality_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- add17a9bc9297ed345ad6f103c6b3525c34fc80b5dcc87083f9f6363ad498c6f
- Size of remote file:
- 1.11 GB
- SHA256:
- 07e30ce0912b6f54705ea6e46781715f422019852d8842b8673a93f8ef23b02b
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