Tsinghua College’s Data Engineering Group (KEG) has unveiled GLM-4 9B, a robust new language mannequin that outperforms GPT-4 and Gemini in numerous benchmarks. Developed by the Tsinghua Deep Mannequin (THUDM) group, this open-source mannequin marks a major milestone within the subject of pure language processing.
At its core, GLM-4 9B is an enormous language mannequin skilled on an unprecedented 10 trillion tokens spanning 26 languages. It caters to numerous capabilities, together with multi-round dialogue in Chinese language and English, code execution, net looking, and customized instrument calling via Perform Name.
The mannequin’s structure is constructed upon the newest developments in deep studying, incorporating cutting-edge methods corresponding to consideration mechanisms and transformer architectures. The bottom model helps a context window of as much as 128,000 tokens, whereas a specialised variant permits for a powerful 1 million token context size.
In comparison with business giants like GPT and Gemini, GLM-4 9B’s structure stands out with its assist for high-resolution imaginative and prescient duties (as much as 1198 x 1198 pixels) and its capacity to deal with a various vary of languages. This versatility positions GLM-4 9B as a robust contender within the language mannequin panorama.
Evaluations on numerous datasets have demonstrated GLM-4 9B’s superior efficiency in lots of areas and efficiency on par with the perfect fashions for a few of the duties, the mannequin has surpassed each different current mannequin on total accuracy. Notably, it has outperformed GPT-4, Gemini Professional (in imaginative and prescient duties), Mistral, and Llama 3 8B, solidifying its place as a formidable drive within the subject.
With its open-source nature and permissive business use (below sure situations), GLM-4 9B presents a wealth of alternatives for builders, researchers, and companies alike. Potential functions vary from pure language processing duties to pc imaginative and prescient, code era, and past. The mannequin’s seamless integration with the Transformers library additional simplifies its adoption and deployment.
The discharge of GLM-4 9B by Tsinghua College’s KEG marks a major milestone in language fashions. With its spectacular efficiency, multi-lingual capabilities, and versatile structure, this mannequin units a brand new benchmark for open-source language fashions and paves the best way for additional developments in pure language processing and synthetic intelligence.
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