Merge pull request #38 from codefuse-ai/jglee2046-patch-1

Update README.md

Author: AntLab-RI

README.md

@@ -47,7 +47,7 @@
 ## News
 🔥🔥 [2024/01/17] We released MFTCoder v0.3.0, mainly for MFTCoder-accelerate. It now supports new models like Mixtral(MoE), DeepSeek-coder, chatglm3. It supports FSDP as an option. It also supports Self-paced Loss as a solution for convergence balance in Multitask Fine-tuning.
 
-🔥🔥 [2024/01/17] [CodeFuse-DeepSeek-33B](https://huggingface.co/codefuse-ai/CodeFuse-DeepSeek-33B) has been released, achieving a pass@1 (greedy decoding) score of 78.7% on HumanEval. It achieves top1 win-rate on Bigcode Leardboard.
+🔥🔥 [2024/01/17] [CodeFuse-DeepSeek-33B](https://huggingface.co/codefuse-ai/CodeFuse-DeepSeek-33B) has been released, achieving a pass@1 (greedy decoding) score of 78.7% on HumanEval. It lists as top-1 LLM on Bigcode Leardboard in terms of win-rate.
 
 🔥🔥 [2024/01/17] [CodeFuse-Mixtral-8x7B](https://huggingface.co/codefuse-ai/CodeFuse-Mixtral-8X7B) has been released, achieving a pass@1 (greedy decoding) score of 56.1% on HumanEval.
 
@@ -61,18 +61,18 @@
 
 🔥🔥🔥 [2023/09/07]We released **CodeFuse-CodeLlama-34B**, which achieves the **74.4% Python Pass@1** (greedy decoding) and surpasses GPT4 (2023/03/15) and ChatGPT-3.5 on the [HumanEval Benchmarks](https://github.com/openai/human-eval).
 
-🔥🔥 [2023/08/26]We released MFTCoder which supports finetuning Code Llama, Llama, Llama2, StarCoder, ChatGLM2, CodeGeeX2, Qwen, and GPT-NeoX models with LoRA/QLoRA.
+🔥🔥 [2023/08/26]We released MFTCoder-v0.1 which supports finetuning Code Llama, Llama, Llama2, StarCoder, ChatGLM2, CodeGeeX2, Qwen, and GPT-NeoX models with LoRA/QLoRA.
 
 ### HumanEval Performance
 | Model                       | HumanEval(Pass@1) |  Date   | 
 |:----------------------------|:-----------------:|:-------:|
 | **CodeFuse-DeepSeek-33B**        |     **78.7%**     | 2024/01 |
-| **CodeFuse-Mixtral-8x7B**        |     **56.1%**     | 2024/01 |
 | **CodeFuse-CodeLlama-34B**       |     **74.4%**     | 2023/09 |
 | **CodeFuse-CodeLlama-34B-4bits** |     **73.8%**     | 2023/09 |
 | WizardCoder-Python-34B-V1.0      |       73.2%       | 2023/08 |
 | GPT-4(zero-shot)                 |       67.0%       | 2023/03 |
 | PanGu-Coder2 15B                 |       61.6%       | 2023/08 |
+| **CodeFuse-Mixtral-8x7B**        |     **56.1%**     | 2024/01 |
 | **CodeFuse-StarCoder-15B**       |     **54.9%**     | 2023/08 |
 | CodeLlama-34b-Python             |       53.7%       | 2023/08 |
 | **CodeFuse-QWen-14B**            |     **48.8%**     | 2023/10 |