Describe usage via sentence-transformers CrossEncoder 4d6f3df
Tom Aarsen commited on
How to use jinaai/jina-reranker-v2-base-multilingual with Transformers:
# Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("jinaai/jina-reranker-v2-base-multilingual", trust_remote_code=True, device_map="auto")How to use jinaai/jina-reranker-v2-base-multilingual with Transformers.js:
// npm i @huggingface/transformers
import { pipeline } from '@huggingface/transformers';
// Allocate pipeline
const pipe = await pipeline('text-ranking', 'jinaai/jina-reranker-v2-base-multilingual');How to use jinaai/jina-reranker-v2-base-multilingual with sentence-transformers:
from sentence_transformers import CrossEncoder
model = CrossEncoder("jinaai/jina-reranker-v2-base-multilingual", trust_remote_code=True)
query = "Which planet is known as the Red Planet?"
passages = [
"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.",
"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
]
scores = model.predict([(query, passage) for passage in passages])
print(scores)