Update README.md

README.md

@@ -8,11 +8,13 @@ pipeline_tag: question-answering
 tags:
 - biology
 - medical
+datasets:
+- shellwork/ChatParts_Dataset
 ---
 
 # shellwork/ChatParts-llama3.1-8b
 
-🤖 [XJTLU-Software RAG GitHub Repository](https://github.com/shellwork/XJTLU-Software-RAG/tree/main) • 📊 [ChatParts Dataset](https://www.modelscope.cn/datasets/shellwork/ChatParts_Dataset)
+🤖 [XJTLU-Software RAG GitHub Repository](https://github.com/shellwork/XJTLU-Software-RAG/tree/main) • 📊 [ChatParts Dataset](https://huggingface.co/datasets/shellwork/ChatParts_Dataset)
 
 **shellwork/ChatParts-llama3.1-8b** is a specialized dialogue model fine-tuned from **Meta-Llama-3.1-8B-Instruct** by the XJTLU-Software iGEM Competition team. This model is tailored for the synthetic biology domain, aiming to assist competition participants and researchers in efficiently collecting and organizing relevant information. It serves as the local model component of the XJTLU-developed Retrieval-Augmented Generation (RAG) software, enhancing search and summarization capabilities within synthetic biology data.
 
@@ -24,7 +26,7 @@ The model is trained on a comprehensive synthetic biology-specific dataset curat
 - **Synthetic Biology Review Papers:** More than 1,000 high-quality review articles providing in-depth insights into various aspects of synthetic biology.
 - **iGEM Parts Registry Documentation:** Detailed documentation of parts used in iGEM projects, facilitating accurate information retrieval.
 
-In total, the dataset comprises over **200,000 question-answer pairs**, meticulously assembled to cover a wide spectrum of synthetic biology topics. For more detailed information about the dataset, please visit our [training data repository](https://github.com/shellwork/XJTLU-Software-RAG/tree/main).
+In total, the dataset comprises over **200,000 question-answer pairs**, meticulously assembled to cover a wide spectrum of synthetic biology topics. For more detailed information about the dataset, please visit our [training data repository](https://huggingface.co/datasets/shellwork/ChatParts_Dataset).
 
 ## 🛠️ How to Use
 
@@ -81,12 +83,12 @@ print("Context (divided into sentences):\n{}\n".format(result['splited_context']
 
 ## 📄 License
 
-This model is released under the **Llama-3.1 License**. For more details, please refer to the [license information](https://www.modelscope.cn/models/llm-research/meta-llama-3.1-8b-instruct) in the repository.
+This model is released under the **Llama-3.1 License**. For more details, please refer to the [license information](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) in the repository.
 
 ## 🔗 Additional Resources
 
 - **RAG Software:** Explore the full capabilities of our Retrieval-Augmented Generation software [here](https://github.com/shellwork/XJTLU-Software-RAG/tree/main).
-- **Training Data:** Access and review the extensive training dataset [here](https://www.modelscope.cn/datasets/shellwork/ChatParts_Dataset) .
+- **Training Data:** Access and review the extensive training dataset [here](https://huggingface.co/datasets/shellwork/ChatParts_Dataset) .
 - **Support & Contributions:** For support or to contribute to the project, visit our [GitHub Issues](https://github.com/shellwork/XJTLU-Software-RAG/issues) page.