Update README.md

README.md

@@ -1,39 +1,40 @@
----
-license: apache-2.0
-language:
-- en
-base_model:
-- Qwen/Qwen3-Embedding-8B
----
-## LEXA-8B
-👉 **LEXA-8B**: LEXA: Legal Case Retrieval via Graph Contrastive Learning with Contextualised LLM Embeddings. More information is available in [**arXiv**](https://arxiv.org/abs/2405.11791) & [**GitHub**](https://github.com/yanran-tang/CaseGNN).
-
-## Example Usage
-
-```python
-from transformers import AutoModel, AutoTokenizer
-model = AutoModel.from_pretrained("AnnaStudy/LEXA-8B", torch_dtype="auto", device_map="auto")
-tokenizer = AutoTokenizer.from_pretrained("AnnaStudy/LEXA-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
-{LEXA-8B,
-author = {Yanran Tang, Ruihong Qiu, Xue Li, Zi Huang},
-title = {LEXA: Legal Case Retrieval via Graph Contrastive Learning with Contextualised LLM Embeddings},
-journal = {CoRR},
-volume = {abs/2405.11791},
-year = {2025}
-}
+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-Embedding-8B
+---
+## LEXA-8B
+![LEXA-8B](LEXA.jpg)
+👉 **LEXA-8B**: LEXA: Legal Case Retrieval via Graph Contrastive Learning with Contextualised LLM Embeddings. More information is available in [**arXiv**](https://arxiv.org/abs/2405.11791) & [**GitHub**](https://github.com/yanran-tang/CaseGNN).
+
+## Example Usage
+
+```python
+from transformers import AutoModel, AutoTokenizer
+model = AutoModel.from_pretrained("AnnaStudy/LEXA-8B", torch_dtype="auto", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("AnnaStudy/LEXA-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
+{LEXA-8B,
+author = {Yanran Tang, Ruihong Qiu, Xue Li, Zi Huang},
+title = {LEXA: Legal Case Retrieval via Graph Contrastive Learning with Contextualised LLM Embeddings},
+journal = {CoRR},
+volume = {abs/2405.11791},
+year = {2025}
+}
 ```