Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
sequence-classification
xlm-roberta-base
faq
questions
text-embeddings-inference
Instructions to use timpal0l/xlm-roberta-base-faq-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use timpal0l/xlm-roberta-base-faq-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="timpal0l/xlm-roberta-base-faq-extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("timpal0l/xlm-roberta-base-faq-extractor") model = AutoModelForSequenceClassification.from_pretrained("timpal0l/xlm-roberta-base-faq-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5029803d8d1a242b65c08d1f8ca4e73bfdec8fc79680343cd9999df859c15c49
- Size of remote file:
- 9.08 MB
- SHA256:
- f9f761e0e122116627dac81039f134bed26d85535a2903d7ff05a1f8f3926ad5
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