Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
mteb
sentence-transfomres
Eval Results (legacy)
text-embeddings-inference
Instructions to use BAAI/bge-large-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/bge-large-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-large-en")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-large-en") model = AutoModel.from_pretrained("BAAI/bge-large-en") - Inference
- Notebooks
- Google Colab
- Kaggle
Can we train cross encoder using this model?
#4
by amkorba - opened
I have a bi encoder trained on bge-large-en which is pretrained and finetuned on domain data.
I want to have a cross encoder to enhance ranking , can i use Sentence_Transfomer cross encoder to train this ?
Bi-encoder and cross-encoder are very different. It may not be a good choice to train cross-encoder using bge. I prefer to use other pre-trained models, such as electra, deberta.
But you can use this bi-encoder to generate candidates which can be used to train cross-encoder.