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:
- 5b0a305ee4ef8e70805ba2f0fca763d9d8a4f07c5a4d6f1b1981ee69f8b00fc2
- Size of remote file:
- 1.11 GB
- SHA256:
- d3cc5eab5ee1eeac52c0aa04b9b4696ca895dac3e74d21a07bb61703e9cdae93
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