Text Ranking
Transformers
ONNX
Safetensors
Transformers.js
sentence-transformers
English
deberta-v2
text-classification
reranker
text-embeddings-inference
Instructions to use mixedbread-ai/mxbai-rerank-large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mixedbread-ai/mxbai-rerank-large-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mixedbread-ai/mxbai-rerank-large-v1") model = AutoModelForSequenceClassification.from_pretrained("mixedbread-ai/mxbai-rerank-large-v1") - Transformers.js
How to use mixedbread-ai/mxbai-rerank-large-v1 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-ranking', 'mixedbread-ai/mxbai-rerank-large-v1'); - sentence-transformers
How to use mixedbread-ai/mxbai-rerank-large-v1 with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("mixedbread-ai/mxbai-rerank-large-v1") 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) - Notebooks
- Google Colab
- Kaggle
add AIBOM
#10 opened 11 months ago
by
sabato-nocera
Usage of mixbread-ai's reranking models for symmetric and asymmetric searches
#8 opened over 1 year ago
by
crestero
Deployment using TEI
3
#7 opened over 1 year ago
by
WolfAssi285