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-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mixedbread-ai/mxbai-rerank-base-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mixedbread-ai/mxbai-rerank-base-v1") model = AutoModelForSequenceClassification.from_pretrained("mixedbread-ai/mxbai-rerank-base-v1", device_map="auto") - Transformers.js
How to use mixedbread-ai/mxbai-rerank-base-v1 with Transformers.js:
// npm i @huggingface/transformers import { AutoTokenizer, AutoModelForSequenceClassification } from '@huggingface/transformers'; const tokenizer = await AutoTokenizer.from_pretrained('mixedbread-ai/mxbai-rerank-base-v1'); const model = await AutoModelForSequenceClassification.from_pretrained('mixedbread-ai/mxbai-rerank-base-v1'); const query = 'Which planet is known as the Red Planet?'; const documents = [ 'Mars, known for its reddish appearance, is often referred to as the Red Planet.', 'Venus is often called the twin of Earth because of its similar size and proximity.', ]; const inputs = tokenizer(new Array(documents.length).fill(query), { text_pair: documents, padding: true, truncation: true }); const { logits } = await model(inputs); console.log(logits.sigmoid().tolist()); // one relevance score per document - sentence-transformers
How to use mixedbread-ai/mxbai-rerank-base-v1 with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("mixedbread-ai/mxbai-rerank-base-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) - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from mixedbread-ai/mxbai-rerank-base-v1: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/mixedbread-ai/mxbai-rerank-base-v1/resolve/main/model.safetensors
- Command line
-
hf download hf://mixedbread-ai/mxbai-rerank-base-v1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mixedbread-ai/mxbai-rerank-base-v1/resolve/main/model.safetensors
369 MB
- Xet hash:
- 38957d6f2718bc4e16776ce444cd18ff657d5038f891176cdb4cbec641984d0d
- Size of remote file:
- 369 MB
- SHA256:
- d9db29f75d900055e9ce4f9a79c841d13384fdc3ca144404f9eecb873fc4fcbd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.