Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Cheng98/bert-base-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-base-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-base-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-base-qqp") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-base-qqp") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "train_loss": 0.16809054645142282, | |
| "train_runtime": 5346.9121, | |
| "train_samples": 363846, | |
| "train_samples_per_second": 340.239, | |
| "train_steps_per_second": 21.266 | |
| } |