Update README.md

README.md

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 # Model Card for Deita 7B V1.0
 
+[GitHub](https://github.com/hkust-nlp/deita) | [Paper](https://arxiv.org/abs/2312.15685)
+
 Deita is an open-sourced project designed to facilitate **Automatic Data Selection** for instruction tuning in Large Language Models (LLMs). 
 Deita 7B V1.0 is a fine-tuned + DPO version of Mistral-7B-v0.1 that was trained on **6K** automatically selected lightweight, high-quality alignment SFT data: [Deita 6K V0](https://huggingface.co/datasets/hkust-nlp/deita-6k-v0) and **10K** randomly sampled alignment preference data from Ultrafeedback.
 
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 ## Performance
 
 
-<details>
-  <summary>See full evaluations</summary>
+
 
 | Model                                          | Align     | Data Size  | MT-Bench | AlpacaEval(%) | OpenLLM (Avg.) |
 |------------------------------------------------|-----------|------------|----------|---------------|----------------|
@@ -63,7 +64,6 @@ Deita 7B V1.0 is a fine-tuned + DPO version of Mistral-7B-v0.1 that was trained
 | DEITA-7B-v1.0             | SFT + DPO | 6K SFT + 10K DPO   | 7.55     | 90.06         | 69.86          |
 
 
-</details>
 
 
 ## Input Format