Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 license: llama3
-base_model: meta-llama/Meta-Llama-3-8B
+base_model: Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.1
 tags:
 - alignment-handbook
 - axolotl
@@ -34,7 +34,7 @@ Codes: [https://github.com/magpie-align/magpie](https://github.com/magpie-align/
 ## Model Overview
 
 This model is an aligned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B). We apply the following pipeline:
-- We first use [Magpie-Align/Magpie-Pro-MT-300K-v0.1](https://huggingface.co/datasets/Magpie-Align/Magpie-Pro-MT-300K-v0.1) dataset and perform SFT -> [Magpie-Align/Llama-3-8B-Magpie-Pro-MT-SFT-v0.1](https://huggingface.co/Magpie-Align/Llama-3-8B-Magpie-Pro-MT-SFT-v0.1)
+- We first use [Magpie-Align/Magpie-Pro-MT-300K-v0.1](https://huggingface.co/datasets/Magpie-Align/Magpie-Pro-MT-300K-v0.1) dataset and perform SFT -> [Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.1](https://huggingface.co/Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.1)
 - We then perform DPO on the [princeton-nlp/llama3-ultrafeedback](https://huggingface.co/datasets/princeton-nlp/llama3-ultrafeedback) dataset.
 
 The overall performance is even better than the official Llama-3-8B-Instruct Model!