instruct-eval
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Evaluate on a single 24GB/32GB GPU
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
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
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