ChatGLM3-6B is a powerful open-source bilingual (Chinese-English) dialogue model based on the General Language Model (GLM) architecture. Developed by Zhipu AI and Tsinghua University, it features 6.2 billion parameters and offers lower deployment requirements compared to larger models. Running this...
Dataset Preparation The experiment utilizes the LLaMA-Factory framwork to perform named entity recognition (NER) on the ChatGLM3-6B model. All resources related to this task—datasets, LoRA fine-tuning scripts, deployment configurations, inference code, prediction results, and evaluation metrics—are...
Local Model Deployment First, acquire the ChatGLM3-6B model. It can be downloaded from its GitHub repository or the Hugging Face Hub. After downloading, set up a Python virtual environment and install the necessary dependencies. LORA Fine-Tuning Dataset Preparation Construct a dataset in a conversat...