---
license: apache-2.0
language:
- en
base_model:
- Qwen/Qwen3-Embedding-8B
---
## ReaKase-8B
![ReaKase-8B](ReaKase.png)
👉 **ReaKase-8B**: Legal Case Retrieval via Knowledge and Reasoning Representations with LLMs. More information is available in [**arXiv**](https://arxiv.org/abs/2510.26178) & [**GitHub**](https://github.com/yanran-tang/ReaKase-8B).

## Example Usage

```python
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("AnnaStudy/ReaKase-8B", torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("AnnaStudy/ReaKase-8B")

case_txt = "The following contains key components of a legal case. Legal facts..."

tokenized = tokenizer(case_txt, return_tensors='pt', padding=True, truncation=True, max_length=2048)
outputs = model(**tokenized)
case_embedding = outputs.last_hidden_state[:, -1]
```
## Base Model

ReaKase-8B is finetuned from **Qwen3-Embedding-8B**, which provides the underlying semantic representation capability.

Reference: [Qwen/Qwen3-Embedding-8B](https://huggingface.co/Qwen/Qwen3-Embedding-8B)

## Cite
If you find this repo useful, please cite
```
@article
{ReaKase-8B,
author = {Yanran Tang, Ruihong Qiu, Xue Li, Zi Huang},
title = {ReaKase-8B: Legal Case Retrieval via Knowledge and Reasoning Representations with LLMs},
journal = {CoRR},
volume = {abs/2510.26178},
year = {2025}
}
```