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tensor parallelism across multiple GPU's #1092
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@samanthvishwas If you only want to load one copy of the model, you can set the following in
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@samanthvishwas Closing the issue. Please open a new one, if you have any more questions. |
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I am following the code as mentioned in the AWS documentation to host GPT-J-6B using DJL serving
[ https://github.com/aws/amazon-sagemaker-examples/blob/main/advanced_functionality/pytorch_deploy_large_GPT_model/GPT-J-6B-model-parallel-inference-DJL.ipynb]
Providing a tensor parallelism value as 2 in serving.properties creates 2 copies of the model rather than partitioning model layers across two GPU's . This happens irrespective of using a smaller/larger model.
Instance used :
ml.g4dn.12xlarge
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