Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Cheng98/bert-large-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-large-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-large-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-large-qqp") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-large-qqp") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 5.0, | |
| "train_loss": 0.19827925553449116, | |
| "train_runtime": 10419.4099, | |
| "train_samples": 363846, | |
| "train_samples_per_second": 174.6, | |
| "train_steps_per_second": 10.913 | |
| } |