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:
- 019c9985f87783509dec658d3e724366d7c16c63e9d98721620eb7c1106f39f2
- Size of remote file:
- 1.11 GB
- SHA256:
- 58adb590b14dd2972373483fe9cac352128d951c61edfe902fa687bef354286d
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