Update README.md

README.md

@@ -14,7 +14,7 @@ tasks:
 
 ## Model Description
 
-CodeFuse-DeepSeek-33B-4bits is the 4-bit quantized version of [CodeFuse-DeepSeek-33B](https://modelscope.cn/models/codefuse-ai/CodeFuse-DeepSeek-33B/summary) which is a 33B Code-LLM finetuned by QLoRA on multiple code-related tasks on the base model DeepSeek-Coder-33B. 
+CodeFuse-DeepSeek-33B-4bits is the 4-bit quantized version of [CodeFuse-DeepSeek-33B](https://huggingface.co/codefuse-ai/CodeFuse-DeepSeek-33B) which is a 33B Code-LLM finetuned by QLoRA on multiple code-related tasks on the base model DeepSeek-Coder-33B. 
 
 After undergoing 4-bit quantization, the CodeFuse-DeepSeek-33B-4bits model can be loaded on either a single A10 (24GB VRAM) or an RTX 4090 (24GB VRAM). Moreover, the quantized model still achives an impressive accuracy of 78.05% on the Humaneval pass@1 metric.
 
@@ -34,9 +34,9 @@ After undergoing 4-bit quantization, the CodeFuse-DeepSeek-33B-4bits model can b
 
   🔥🔥 2023-09-27 CodeFuse-StarCoder-15B has been released, achieving a pass@1 (greedy decoding) score of 54.9% on HumanEval, which is a 21% increase compared to StarCoder's 33.6%.
 
-🔥🔥🔥 2023-09-26 We are pleased to announce the release of the [4-bit quantized version](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B-4bits/summary) of [CodeFuse-CodeLlama-34B](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B/summary). Despite the quantization process, the model still achieves a remarkable 73.8% accuracy (greedy decoding) on the HumanEval pass@1 metric.
+🔥🔥🔥 2023-09-26 We are pleased to announce the release of the [4-bit quantized version](https://huggingface.co/codefuse-ai/CodeFuse-CodeLlama-34B-4bits) of [CodeFuse-CodeLlama-34B](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B/summary). Despite the quantization process, the model still achieves a remarkable 73.8% accuracy (greedy decoding) on the HumanEval pass@1 metric.
 
-🔥🔥🔥 2023-09-11 [CodeFuse-CodeLlama34B](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B/summary) has achieved 74.4% of pass@1 (greedy decoding) on HumanEval, which is SOTA results for openspurced LLMs at present.
+🔥🔥🔥 2023-09-11 [CodeFuse-CodeLlama34B](https://huggingface.co/codefuse-ai/CodeFuse-CodeLlama-34B-4bits) has achieved 74.4% of pass@1 (greedy decoding) on HumanEval, which is SOTA results for openspurced LLMs at present.
 
 <br>
 
@@ -209,7 +209,7 @@ if __name__ == "__main__":
 
 ## 模型简介
 
-CodeFuse-DeepSeek-33B-4bits是代码大模型[CodeFuse-DeepSeek-33B](https://modelscope.cn/models/codefuse-ai/CodeFuse-DeepSeek-33B/summary)的4-bits量化版本，后者基于底座模型DeepSeek-Coder-33B使用MFTCoder框架在多个代码相关任务上微调得到。
+CodeFuse-DeepSeek-33B-4bits是代码大模型[CodeFuse-DeepSeek-33B](https://huggingface.co/codefuse-ai/CodeFuse-DeepSeek-33B)的4-bits量化版本，后者基于底座模型DeepSeek-Coder-33B使用MFTCoder框架在多个代码相关任务上微调得到。
 
 经过4-bits量化后，CodeFuse-DeepSeek-33B-4bits可在单张A10 (24GB显存)或者RTX 4090（24G显存）上加载。量化后，CodeFuse-DeepSeek-33B-4bits仍取得HumanEval pass@1 78.05%。
 <br>
@@ -228,9 +228,9 @@ CodeFuse-DeepSeek-33B-4bits是代码大模型[CodeFuse-DeepSeek-33B](https://mod
 
   🔥🔥 2023-09-27开源了CodeFuse-StarCoder-15B模型，在HumanEval pass@1(greedy decoding)上可以达到54.9%, 比StarCoder提高了21%的代码能力（HumanEval）
 
-🔥🔥🔥 2023-09-26 [CodeFuse-CodeLlama-34B 4bits](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B-4bits/summary)量化版本发布，量化后模型在HumanEval pass@1指标为73.8% (贪婪解码)。
+🔥🔥🔥 2023-09-26 [CodeFuse-CodeLlama-34B 4bits](https://huggingface.co/codefuse-ai/CodeFuse-CodeLlama-34B-4bits)量化版本发布，量化后模型在HumanEval pass@1指标为73.8% (贪婪解码)。
 
-🔥🔥🔥 2023-09-11 [CodeFuse-CodeLlama-34B](https://modelscope.cn/models/codefuse-ai/CodeFuse-CodeLlama-34B/summary)发布，HumanEval pass@1指标达到74.4% (贪婪解码), 为当前开源SOTA。
+🔥🔥🔥 2023-09-11 [CodeFuse-CodeLlama-34B](https://huggingface.co/codefuse-ai/CodeFuse-CodeLlama-34B)发布，HumanEval pass@1指标达到74.4% (贪婪解码), 为当前开源SOTA。
 
 <br>