GLM-4-9B-Chat-1M

A new generation of open-source pre-trained model supporting multi-turn dialogue and multilingualism.

PremiumNewProductProgrammingPre-trained ModelMulti-turn Dialogue

GLM-4-9B-Chat-1M is a new generation of pre-trained model released by ZhiPu AI, an open-source version of the GLM-4 series. It has demonstrated high performance in various benchmark datasets covering semantics, mathematics, reasoning, code, and knowledge. This model not only supports multi-turn dialogue but also features advanced functionalities like web browsing, code execution, custom tool invocation, and long-text reasoning. It supports 26 languages, including Japanese, Korean, and German, and a special version with 1M context length is available, suitable for developers and researchers handling large amounts of data and working in multilingual environments.

Multi-turn dialogue capability for coherent interactions.
Web browsing functionality to access and understand web content.
Code execution capability to run and understand code.
Custom tool invocation to integrate and utilize custom tools or APIs.
Long-text reasoning supporting up to 128K context
suitable for processing large datasets.
Multilingual support
including 26 languages such as Japanese
Korean
and German.

This model is primarily designed for developers
data scientists
and researchers who work with complex datasets
require multilingual interactions
or need a model with advanced reasoning and execution capabilities. It can help them increase work efficiency

Developers use this model to build multilingual chatbots.
Data scientists leverage the model's long-text reasoning ability for large-scale data analysis.
Researchers utilize the model's code execution functionality for algorithm validation and testing.

Step 1: Import necessary libraries
such as torch and transformers.
Step 2: Load the model's tokenizer using AutoTokenizer.from_pretrained() method.
Step 3: Prepare input data
format it using tokenizer.apply_chat_template() method.

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20899836

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46.04%

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5.2

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00:04:57

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