Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
multi-vector
ColBERT
text-embeddings-inference
Instructions to use mixedbread-ai/mxbai-colbert-large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mixedbread-ai/mxbai-colbert-large-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mixedbread-ai/mxbai-colbert-large-v1") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
[Using the pre-trained model to get inference via CrossEncoders]
#3 opened about 2 years ago
by
EltonLobo
Question about the mask of query
2
#1 opened over 2 years ago
by
kagaii