Instructions to use BAAI/bge-large-en-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BAAI/bge-large-en-v1.5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BAAI/bge-large-en-v1.5") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use BAAI/bge-large-en-v1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BAAI/bge-large-en-v1.5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-large-en-v1.5") model = AutoModel.from_pretrained("BAAI/bge-large-en-v1.5", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Requesting access to BAAI/bge3-base-en
Hello BAAI team,
I'm currently working on semantic retrieval and schema-level reasoning over relational databases using dense embeddings. I’m very interested in leveraging your bge3-base-en model, as it appears to provide significant improvements in representation quality, particularly with 8192-dimensional outputs.
However, the model currently appears to be private or inaccessible on Hugging Face (404 / unauthorized). Is there any way to request access to this model, or could you please confirm whether it will be publicly released soon?
My Hugging Face username: ssv76
Thank you for your contributions to the community—BGE has been instrumental in my projects.
Best regards,
Sebastian Santa
ON Identity RFID