Instructions to use boronbrown48/1_model_topic_classification_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boronbrown48/1_model_topic_classification_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boronbrown48/1_model_topic_classification_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boronbrown48/1_model_topic_classification_v2") model = AutoModelForSequenceClassification.from_pretrained("boronbrown48/1_model_topic_classification_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 294 Bytes
c826e73 | 1 2 3 4 5 6 7 8 9 | {'epoch': 3.54,
'eval_accuracy': 0.9243642329778508,
'eval_f1-macro': 0.7717268068768623,
'eval_loss': 0.3193516135215759,
'eval_precision': 0.7777396877295429,
'eval_recall': 0.7715675339890613,
'eval_runtime': 76.7377,
'eval_samples_per_second': 79.426,
'eval_steps_per_second': 9.93} |