Update README.md

README.md

@@ -1,3 +1,99 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- retrieval
+- query-rewriting
+- reinforcement-learning
+---
+
+<h1 align="center">INF-Query-Aligner</h1>
+
+<p align="center">
+    <a href="https://brightbenchmark.github.io/"><img src="https://img.shields.io/badge/BRIGHT_Benchmark-Rank_1st-8A2BE2" alt="Rank"></a>
+    <a href="https://huggingface.co/infly/inf-query-aligner"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-INF--Query--Aligner-blue" alt="Hugging Face"></a>
+    <a href="https://opensource.org/licenses/Apache-2.0"><img src="https://img.shields.io/badge/License-Apache--2.0-green.svg" alt="License"></a>
+</p>
+
+## 📖 Overview
+
+**INF-Query-Aligner** is a specialized component of the **INF-X-Retriever** framework, designed to distill the core retrieval intent from complex, verbose, or reasoning-intensive queries. Built upon the **Qwen2.5-7B-instruct** foundation and fine-tuned via Reinforcement Learning, it transforms raw user queries into concise, search-optimized queries for dense retrieval systems.
+
+This model is a key enabler for **INF-X-Retriever**'s state-of-the-art performance, currently holding the **No. 1 position** on the [BRIGHT Benchmark](https://brightbenchmark.github.io/) (as of Dec 17, 2025).
+
+For more details on the full framework, please visit the [INF-X-Retriever Repository](https://github.com/infly/INF-X-Retriever).
+
+---
+
+## 🚀 Quick Start
+
+Below is a simple example of how to use **INF-Query-Aligner** for query rewriting using the `transformers` library.
+
+### Installation
+
+```bash
+pip install transformers==4.51.0
+```
+
+### Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "infly/inf-query-aligner"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Give me a short introduction to large language model."
+messages = [
+    {"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."},
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
+
+---
+
+## 🖊️ Citation
+
+If you find this model useful, please consider citing our work:
+
+```bibtex
+@misc{inf-x-retriever-2025,
+    title        = {INF-X-Retriever},
+    author       = {Yichen Yao, Jiahe Wan, Yuxin Hong, Mengna Zhang, Junhan Yang, Zhouyu Jiang, Qing Xu, Yinghui Xu, Wei Chu, Yuan Qi},
+    year         = {2025},
+    url          = {https://yaoyichen.github.io/INF-X-Retriever},
+    publisher    = {GitHub repository}
+}
+```
+
+---
+
+## 📬 Contact
+
+**Project Lead:** Yichen Yao ([eason.yyc@inftech.ai](mailto:eason.yyc@inftech.ai))
+