Instructions to use boronbrown48/1_topic_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/1_topic_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/1_topic_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/1_topic_classification") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/1_topic_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 298 Bytes
6431b2f | 1 2 3 4 5 6 7 8 9 | {'epoch': 4.13,
'eval_accuracy': 0.9283018867924528,
'eval_f1-macro': 0.7835303930477823,
'eval_loss': 0.31459057331085205,
'eval_precision': 0.7974073129596689,
'eval_recall': 0.7740961320523125,
'eval_runtime': 25.4833,
'eval_samples_per_second': 239.177,
'eval_steps_per_second': 29.902} |