commit from qyj

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README.md

@@ -1,3 +1,48 @@
 ---
-license: apache-2.0
+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
+

added_tokens.json

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config.json

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+  "architectures": [
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+  ],
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+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32001
+}

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+  "transformers_version": "4.36.2"
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