Instructions to use TungLe7661/BERT650 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TungLe7661/BERT650 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TungLe7661/BERT650")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TungLe7661/BERT650") model = AutoModelForSequenceClassification.from_pretrained("TungLe7661/BERT650") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
'eval_accuracy': 0.68516, 'eval_f1': 0.6844490693226439, 'eval_precision': 0.6839923350377614, 'eval_recall': 0.68516
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