Instructions to use boronbrown48/wangchanberta-topic-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/wangchanberta-topic-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/wangchanberta-topic-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/wangchanberta-topic-classification") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/wangchanberta-topic-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 297 Bytes
50fb13f | 1 2 3 4 5 6 7 8 9 | {'epoch': 1.68,
'eval_accuracy': 0.7569043532532377,
'eval_f1-macro': 0.7521077090954053,
'eval_loss': 0.7462636232376099,
'eval_precision': 0.7506802860775812,
'eval_recall': 0.7569043532532377,
'eval_runtime': 25.5598,
'eval_samples_per_second': 250.745,
'eval_steps_per_second': 31.377} |