Zero-Shot Classification
Transformers
Safetensors
PyTorch
English
zero-shot
multi-label
text-classification
Instructions to use polodealvarado/biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use polodealvarado/biencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="polodealvarado/biencoder")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("polodealvarado/biencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "biencoder", | |
| "encoder_name": "bert-base-uncased", | |
| "param_count": 109482240, | |
| "num_steps": 1000, | |
| "best_step": 850, | |
| "batch_size": 2, | |
| "learning_rate": 2e-05, | |
| "train_time_s": 344.99, | |
| "precision": 0.9486, | |
| "recall": 0.966, | |
| "f1": 0.9572 | |
| } |