| language: en | |
| tags: | |
| - bert | |
| - classification | |
| - pytorch | |
| pipeline_tag: text-classification | |
| # BiEncoder Classification Model | |
| This model is a BiEncoder architecture based on BERT for text pair classification. | |
| ## Model Details | |
| - Base Model: bert-base-uncased | |
| - Architecture: BiEncoder with BERT base | |
| - Number of classes: 4 | |
| ## Usage | |
| ```python | |
| from transformers import AutoTokenizer | |
| import torch | |
| # Load tokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("minoosh/bert-clf-biencoder-kl_divergence") | |
| # Load model weights | |
| state_dict = torch.load("pytorch_model.bin") | |
| # Initialize model (you'll need the BiEncoderModel class) | |
| model = BiEncoderModel( | |
| base_model=AutoModel.from_pretrained("bert-base-uncased"), | |
| num_classes=4 | |
| ) | |
| model.load_state_dict(state_dict) | |
| ``` | |