Instructions to use nhanv/VBHC-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/VBHC-classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nhanv/VBHC-classify")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nhanv/VBHC-classify") model = AutoModelForSequenceClassification.from_pretrained("nhanv/VBHC-classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 230 Bytes
824ead0 | 1 2 3 4 5 6 7 8 9 | {
"epoch": 5.0,
"eval_accuracy": 0.9971590909090909,
"eval_loss": 0.012539840303361416,
"eval_runtime": 6.4144,
"eval_samples": 704,
"eval_samples_per_second": 109.753,
"eval_steps_per_second": 13.719
} |