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Hi, on a single 4090 GPU with 24GB memory, the following command will cause out-of-memory.
python main.py mmlu --model_name llama --model_path huggyllama/llama-7b
After that, I try executing the command on A100-40GB, the nvidia-smi result is
nvidia-smi
It seems that neither 4090/3090 with 24GB memory or V100 with 32GB memory cannot test Llama-7B on mmlu under above command.
So how to evaluate llama-7b on mmlu on 24GB or 32GB GPU? any more options to enable?
Thanks
The text was updated successfully, but these errors were encountered:
It seems that the CUDA memory will increase during execution of the script
Maybe related to maximum sequence length
Finally, the inference can be finished on a single A100-40GB card
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Hi, on a single 4090 GPU with 24GB memory, the following command will cause out-of-memory.
After that, I try executing the command on A100-40GB, the
nvidia-smi
result isIt seems that neither 4090/3090 with 24GB memory or V100 with 32GB memory cannot test Llama-7B on mmlu under above command.
So how to evaluate llama-7b on mmlu on 24GB or 32GB GPU? any more options to enable?
Thanks
The text was updated successfully, but these errors were encountered: