Long-Context Generation is a critical aspect in various applications, such as document summarization, extended conversation handling, and complex question answering. Effective long-context generation can lead to more coherent and contextually relevant responses, enhancing user experience and model utility.
This folder contains examples of running long-context generation with IPEX-LLM on Intel Arc™ A770 Graphics(16GB GPU memory):
- LLaMA2-32K: examples of running LLaMA2-32K models with INT4/FP8 precision.
- ChatGLM3-32K: examples of running ChatGLM3-32K models with INT4/FP8 precision.
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INT4
Model Name Low Memory Mode Maximum Input Length Output Length LLaMA2-7B-32K Disable 10K 512 Enable 12K 512 ChatGLM3-6B-32K Disable 9K 512 Enable 10K 512 -
FP8
Model Name Low Memory Mode Maximum Input Length Output Length LLaMA2-7B-32K Disable 7K 512 Enable 9K 512 ChatGLM3-6B-32K Disable 8K 512 Enable 9K 512
Note: If you need to run longer input or use less memory, please set
IPEX_LLM_LOW_MEM=1
to enable low memory mode, which will enable memory optimization and may slightly affect the performance.