Introduction to GLM-4 Project
The GLM-4 project represents a significant advancement in pre-trained models developed by Zhipu AI. This project focuses on a wide range of capabilities, from language understanding to mathematical problem solving, and even multi-modal communication. Here's an in-depth look into what makes GLM-4 intriguing and powerful.
Project Updates
- Release of GLM-4-Voice: On October 25, 2024, the team launched an end-to-end model for English and Chinese voice conversations called GLM-4-Voice.
- OpenAI API Compatibility: In September 2024, the project enhanced the GLM-4v-9B model support for the vllm framework and built a service compatible with the OpenAI API.
- Long Text Capabilities: In August 2024, the project team introduced LongWriter-GLM4-9B, which can generate text outputs exceeding 10,000 tokens in a single interaction.
- Technical Reports and Model Improvements: Throughout 2024, the team has been consistently working with technical giants like Intel to enhance deployment on various hardware, making it efficient and robust.
Model Overview
GLM-4-9B is a standout in the GLM series, established as an open-source model version that overtakes competitors such as Llama-3-8B in numerous performance tests. Boasting multi-round conversation abilities, the model also supports web browsing, code execution, long-text reasoning, and can operate across 26 languages. Noteworthy is the GLM-4-9B-Chat-1M, capable of managing one million context tokens, and the GLM-4V-9B, a multi-modal model that excels in visual understanding.
Model List
Several models make up the GLM-4 series. These include the base model GLM-4-9B with an 8K sequence length, and more advanced versions like GLM-4-9B-Chat with a 128K context length, GLM-4-9B-Chat-1M for extended context processing, and the multi-modal GLM-4V-9B.
Evaluation Results
Dialogue Model Tasks
GLM-4 models have been rigorously tested across various benchmark tasks such as alignments, mathematical reasoning, and code evaluations. The GLM-4-9B-Chat model has consistently outperformed others in tasks like AlignBench and MMLU.
Long Text Capabilities
For long context tasks, it excels in experimental setups like needle-in-a-haystack scenarios, showing superior performance in handling extensive texts.
Multi-language Skills
GLM-4-9B-Chat demonstrates strong performance across multilingual datasets, showing considerable improvement over models like Llama-3-8B-Instruct in many languages.
Functionality and Tool Usage
The GLM-4 models also shine in their ability to call and use tools effectively, showing capabilities nearly on par with leading models such as GPT-4.
Multi-modal Abilities
The GLM-4V-9B model showcases strong multi-modal capabilities, being able to understand and perform tasks involving visual data, making it a competitive player in tasks alongside models like GPT-4 and others.
Quick Start
For those interested in utilizing GLM-4-9B-Chat, the setup involves straightforward processes using popular machine learning frameworks and inferences. Detailed hardware requirements and setup instructions are provided to facilitate easy deployment.
In summary, the GLM-4 project signifies a leap forward in the AI modeling domain, with its wide-ranging abilities in both language and multi-modal environments. This makes it a critical asset for developers and researchers aiming for cutting-edge AI applications.