Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Minh64/XLM_Domain_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Minh64/XLM_Domain_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Minh64/XLM_Domain_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Minh64/XLM_Domain_classifier") model = AutoModelForSequenceClassification.from_pretrained("Minh64/XLM_Domain_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 773633d6cc791531ad2027a39edfc20c4353e920beee25f59795805befd9df10
- Size of remote file:
- 1.11 GB
- SHA256:
- d557c855d0b0262b30fabbf6a80dab16bdf4c8fe52d52fc1f397803509154648
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