Update README.md

README.md

@@ -1,48 +1,49 @@
----
-license: llama2
-datasets:
-- ACE05
-- conll2003
-- conll2012_ontonotesv5
-- rams
-- tacred
-- fewrel
-- maven
-language:
-- en
-metrics:
-- f1
-pipeline_tag: text-generation
-tags:
-- text-generation-inference
-- Information Extraction
-- IE
-- Named Entity Recogniton
-- Event Extraction
-- Relation Extraction
-- LLaMA
----
-
-# Model Card for ADELIE-SFT
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-<p align="justify">
-We introduce <b>ADELIE</b> (<b>A</b>ligning large language mo<b>DEL</b>s on <b>I</b>nformation <b>E</b>xtraction), an aligned LLM that effectively solves various IE tasks, including closed IE, open IE, and on-demand IE. We first collect and construct a high-quality alignment corpus <font face="Verdana">IEInstruct</font> for IE. Then we train ADELIE<sub>SFT</sub> using instruction tuning on <font face="Verdana">IEInstruct</font>. We further train ADELIE<sub>SFT</sub> with direct preference optimization (DPO) objective, resulting in ADELIE<sub>DPO</sub>. Extensive experiments on various held-out IE datasets demonstrate that our models (ADELIE<sub>SFT</sub> and ADELIE<sub>DPO</sub>) achieve state-of-the-art (SoTA) performance among open-source models. We further explore the general capabilities of ADELIE, and experimental results reveal that their general capabilities do not exhibit a noticeable decline.
-
-- 📖 Paper: [ADELIE: Aligning Large Language Models on Information Extraction](https://arxiv.org/abs/2405.05008)
-</p>
-
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** Yunjia Qi, Hao Peng, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
-- **Model type:** Text Generation
-- **Language(s) (NLP):** English
-- **License:** LLaMA2 License for the base model. 
-- **Finetuned from model [optional]:** LLaMA2-7B
-
+---
+license: llama2
+datasets:
+- ACE05
+- conll2003
+- conll2012_ontonotesv5
+- rams
+- tacred
+- fewrel
+- maven
+language:
+- en
+metrics:
+- f1
+pipeline_tag: text-generation
+tags:
+- text-generation-inference
+- Information Extraction
+- IE
+- Named Entity Recogniton
+- Event Extraction
+- Relation Extraction
+- LLaMA
+---
+
+# Model Card for ADELIE-SFT
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+<p align="justify">
+We introduce <b>ADELIE</b> (<b>A</b>ligning large language mo<b>DEL</b>s on <b>I</b>nformation <b>E</b>xtraction), an aligned LLM that effectively solves various IE tasks, including closed IE, open IE, and on-demand IE. We first collect and construct a high-quality alignment corpus <font face="Verdana">IEInstruct</font> for IE. Then we train ADELIE<sub>SFT</sub> using instruction tuning on <font face="Verdana">IEInstruct</font>. We further train ADELIE<sub>SFT</sub> with direct preference optimization (DPO) objective, resulting in ADELIE<sub>DPO</sub>. Extensive experiments on various held-out IE datasets demonstrate that our models (ADELIE<sub>SFT</sub> and ADELIE<sub>DPO</sub>) achieve state-of-the-art (SoTA) performance among open-source models. We further explore the general capabilities of ADELIE, and experimental results reveal that their general capabilities do not exhibit a noticeable decline.
+
+- 📖 Paper: [ADELIE: Aligning Large Language Models on Information Extraction](https://arxiv.org/abs/2405.05008)
+</p>
+- 🐧 github: [THU/ADELIE](https://github.com/THU-KEG/ADELIE/tree/main)
+
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Yunjia Qi, Hao Peng, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
+- **Model type:** Text Generation
+- **Language(s) (NLP):** English
+- **License:** LLaMA2 License for the base model. 
+- **Finetuned from model [optional]:** LLaMA2-7B
+