Feature Extraction
sentence-transformers
PyTorch
ONNX
Safetensors
Transformers
English
bert
sentence-similarity
mteb
Eval Results (legacy)
Eval Results
text-embeddings-inference
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
Has this been trained on code?
#7
by juskazan - opened
I see it has been trained on stack exchange, was stack overflow a part of it? I'm thinking of using it to embed code chunks.
There are some data in the training data, but the quality of code embedding may not be good because the code data is not very much.
Thank you