mirror of
https://github.com/OpenBMB/MiniCPM-V.git
synced 2026-02-05 02:09:20 +08:00
42 lines
1.6 KiB
Bash
42 lines
1.6 KiB
Bash
export PATH=/usr/local/cuda/bin:$PATH
|
|
|
|
export HF_ENDPOINT=https://hf-mirror.com
|
|
export OMP_NUM_THREADS=1
|
|
export timestamp=`date +"%Y%m%d%H%M%S"`
|
|
export OLD_VERSION='False'
|
|
export PYTHONPATH=$(dirname $SELF_DIR):$PYTHONPATH
|
|
export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
|
|
|
|
# gpu consumed
|
|
# fp16 17-18G
|
|
# int4 7-8G
|
|
|
|
# model to be used
|
|
# Example: MODELNAME=MiniCPM-o-2_6
|
|
MODELNAME=$1
|
|
# datasets to be tested
|
|
# Example: DATALIST=MMMU_DEV_VAL
|
|
DATALIST=$2
|
|
|
|
# run on multi gpus with torchrun command
|
|
# remember to run twice, the first run may fail
|
|
for DATASET in $DATALIST; do
|
|
echo "Starting inference with model $MODELNAME on dataset $DATASET"
|
|
torchrun --master_port 29500 --nproc_per_node=8 run.py --data $DATASET --model $MODELNAME --mode infer --reuse
|
|
torchrun --master_port 29501 --nproc_per_node=8 run.py --data $DATASET --model $MODELNAME --mode infer --reuse
|
|
|
|
# for benchmarks which require gpt for scoring, you need to specify OPENAI_API_BASE and OPENAI_API_KEY in .env file
|
|
if [[ "$DATASET" == *"MMBench_TEST"*]]; then
|
|
echo "Skipping evaluation for dataset $DATASET"
|
|
else
|
|
echo "Starting evaluation with model $MODELNAME on datasets $DATASET"
|
|
python run.py --data $DATASET --model $MODELNAME --nproc 16 --verbose
|
|
fi
|
|
done
|
|
|
|
# run on single gpu with python command
|
|
# python run.py --data $DATALIST --model $MODELNAME --verbose --mode infer
|
|
# python run.py --data $DATALIST --model $MODELNAME --verbose --mode infer
|
|
# echo "Starting evaluation with model $MODELNAME on datasets $DATASET"
|
|
# python run.py --data $DATASET --model $MODELNAME --nproc 16 --verbose
|