sentence-transformers
ONNX
Safetensors
ColBERT
multi-vector
passage-retrieval
custom_code
🇪🇺 Region: EU
Instructions to use jinaai/jina-colbert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jinaai/jina-colbert-v2 with sentence-transformers:
from sentence_transformers import MultiVectorEncoder model = MultiVectorEncoder("jinaai/jina-colbert-v2", trust_remote_code=True) queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Notebooks
- Google Colab
- Kaggle
better behavior when query_prefix or document_prefix delete
#21 opened about 1 year ago
by
chenxiaobin
How to fine-tuned this model
#20 opened over 1 year ago
by
kimleang123
add AIBOM
#18 opened over 1 year ago
by
sabato-nocera
how to use onnx
#17 opened over 1 year ago
by
qnguyen3
Official API does not automaticly truncate long doc but returns 400 Client Error
1
#16 opened over 1 year ago
by
ocean11
Is it possible to filter out irrelevant documents based on sum of the score?
#13 opened about 2 years ago
by
nyust-eb210
Help. Load model failed using pylate
2
#12 opened about 2 years ago
by
iheycc
This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module
#7 opened about 2 years ago
by
Guangchao007
Errors on The state dictionary
5
#4 opened about 2 years ago
by
baconnier