jina-reranker-v1-turbo-en

jina-reranker-v1-turbo-en 项目介绍

项目背景

jina-reranker-v1-turbo-en 是由 Jina AI 开发的一个高性能排序模型。它建立在JinaBERT模型的基础上，通过使用对称双向的ALiBi技术，可以处理最长达 8192 个 token 的文本序列，适用于复杂文本排序任务。

核心技术与优势

为了实现超快的处理速度，jina-reranker-v1-turbo-en 使用了一种知识蒸馏技术。这个过程中，一个复杂且较慢的模型被用作“教师”，它将知识浓缩到一个较小且更快的“学生”模型中。这样一来，“学生”模型能够在保持精度的前提下更快地运行。

以下是该模型以及其他相关模型的对比：

jina-reranker-v1-turbo-en 拥有 6 层 和 37.8 百万 参数，在速度与精度之间达到了良好的平衡。而 jina-reranker-v1-tiny-en 则进一步追求速度，以 4 层 和 33.0 百万 参数实现最快的推理速度。

使用方法

1. 使用 Jina AI 的Reranker API：

curl https://api.jina.ai/v1/rerank \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
  "model": "jina-reranker-v1-turbo-en",
  "query": "Organic skincare products for sensitive skin",
  "documents": [
    "Eco-friendly kitchenware for modern homes",
    "Biodegradable cleaning supplies for eco-conscious consumers",
    "Organic cotton baby clothes for sensitive skin",
    "Natural organic skincare range for sensitive skin",
    "Tech gadgets for smart homes: 2024 edition",
    "Sustainable gardening tools and compost solutions",
    "Sensitive skin-friendly facial cleansers and toners",
    "Organic food wraps and storage solutions",
    "All-natural pet food for dogs with allergies",
    "Yoga mats made from recycled materials"
  ],
  "top_n": 3
}'

2. 使用 sentence-transformers 库进行模型交互：

pip install -U sentence-transformers

from sentence_transformers import CrossEncoder

model = CrossEncoder("jinaai/jina-reranker-v1-turbo-en", trust_remote_code=True)

query = "Organic skincare products for sensitive skin"
documents = [
    "Eco-friendly kitchenware for modern homes",
    "Biodegradable cleaning supplies for eco-conscious consumers",
    "Organic cotton baby clothes for sensitive skin",
    "Natural organic skincare range for sensitive skin",
    "Tech gadgets for smart homes: 2024 edition",
    "Sustainable gardening tools and compost solutions",
    "Sensitive skin-friendly facial cleansers and toners",
    "Organic food wraps and storage solutions",
    "All-natural pet food for dogs with allergies",
    "Yoga mats made from recycled materials"
]

results = model.rank(query, documents, return_documents=True, top_k=3)

3. 使用 transformers 库：

!pip install transformers
from transformers import AutoModelForSequenceClassification

model = AutoModelForSequenceClassification.from_pretrained(
    'jinaai/jina-reranker-v1-turbo-en', num_labels=1, trust_remote_code=True
)

4. JavaScript 环境中使用 transformers.js 库：

npm i @xenova/transformers

评估

在评估中，jina-reranker-v1-turbo-en 在三个关键基准上表现优异：

NDCG@10 为排名质量的指标，值越高说明搜索结果越好；Hit Rate 测量在前十个搜索结果中出现相关文档的百分比。

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