Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use cartesinus/xlm-r-base_leyzer_intent-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/xlm-r-base_leyzer_intent-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/xlm-r-base_leyzer_intent-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/xlm-r-base_leyzer_intent-en") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/xlm-r-base_leyzer_intent-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1591cb78e60b8d3a4546e93448718219e36ef37edcbdd4d19e3cac6d35c59363
- Size of remote file:
- 3.45 kB
- SHA256:
- bede0b1b887af8aee4eec6264e8ff48b5746ca818f860284b7c54a785bda1c3a
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