Update README.md

README.md

@@ -1,3 +1,18 @@
+---
+datasets:
+- sciq
+- metaeval/ScienceQA_text_only
+- openbookqa
+- GAIR/lima
+- Open-Orca/OpenOrca
+language:
+- en
+tags:
+- upstage
+- llama
+- instruct
+- instruction
+---
 # LLaMa-30b-instruct model card
 
 **Model Developers**
@@ -41,7 +56,7 @@
 ## Evaluation Results
 
 **Overview**
-- We conducted a performance evaluation based on the tasks being evaluated on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). We evaluated our model on four benchmark datasets, which include ARC-Challenge, HellaSwag, MMLU, and TruthfulQA. We used the lm-evaluation-harness repository, specifically commit b281b0921b636bc36ad05c0b0b0763bd6dd43463. We can reproduce the evaluation environments using the command below:
+- We conducted a performance evaluation based on the tasks being evaluated on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). We evaluated our model on four benchmark datasets, which include ARC-Challenge, HellaSwag, MMLU, and TruthfulQA. We used the lm-evaluation-harness repository, specifically commit `b281b0921b636bc36ad05c0b0b0763bd6dd43463`. We can reproduce the evaluation environments using the command below:
 
 - **Main Results**
 
@@ -64,21 +79,4 @@
 **Why Upstage LLM?**
 - [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. Our 30B model size outperforms all models worldwide with less than 65B, establishing itself as the leading performer. Recognizing the immense potential for private LLM adoption within companies, we invite you to effortlessly implement a private LLM and fine-tune it with your own data. For a seamless and tailored solution, please don't hesitate to reach out to us [(click here to mail)].
 
-[1]: https://en.upstage.ai
-[2]: https://github.com/facebookresearch/llama/tree/llama_v1
-[3]: https://huggingface.co/upstage/llama-30b-instruct
-[4]: https://huggingface.co/upstage/llama-30b-instruct-2048
-[5]: https://huggingface.co/upstage/llama-65b-instruct
-[6]: https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform
-[7]: https://huggingface.co/upstage/llama-30b-instruct-2048/discussions
-[8]: https://huggingface.co/datasets/openbookqa
-[9]: https://huggingface.co/datasets/sciq
-[10]: https://huggingface.co/datasets/Open-Orca/OpenOrca
-[11]: https://huggingface.co/datasets/metaeval/ScienceQA_text_only
-[12]: https://huggingface.co/datasets/GAIR/lima
-[13]: https://github.com/microsoft/DeepSpeed
-[14]: https://huggingface.co/docs/transformers/main_classes/trainer
-[15]: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
-[(click here to mail)]: mailto:contact@upstage.ai
-
-
+[(click here to mail)]: mailto:contact@upstage.ai