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I can not reprduce the results reported from the paper compressing Mistral-7b-v0.1 model under 20% compression ratio and the perplexity seems strange:
PPL after pruning: {'wikitext2': np.float64(330.8548009158036)} Weight Memory: 24960.9072265625 MiB
Below are how i run the code:
COMPRESSION_RATIO=0.2 HUGGINGFACE_MODEL_REPO="mistralai/Mistral-7B-v0.1" WHITENING_SAMPLE_NUMBER=256 WHITENING_DATASET="wikitext2" SAMPLING_SEED=42 MODEL_SEQ_LEN=2048 WHITENING_INFO_SAVING_PATH="."
python SVDLLM.py --step 1 --ratio $COMPRESSION_RATIO --model $HUGGINGFACE_MODEL_REPO --whitening_nsamples $WHITENING_SAMPLE_NUMBER --dataset $WHITENING_DATASET --seed $SAMPLING_SEED --model_seq_len $MODEL_SEQ_LEN --save_path $WHITENING_INFO_SAVING_PATH --DEV cuda:3
python SVDLLM.py --step 4 \ --MODEL_PATH
And i can not run with "low-resource" mode either
The text was updated successfully, but these errors were encountered:
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I can not reprduce the results reported from the paper compressing Mistral-7b-v0.1 model under 20% compression ratio and the perplexity seems strange:
PPL after pruning: {'wikitext2': np.float64(330.8548009158036)}
Weight Memory: 24960.9072265625 MiB
Below are how i run the code:
COMPRESSION_RATIO=0.2
HUGGINGFACE_MODEL_REPO="mistralai/Mistral-7B-v0.1"
WHITENING_SAMPLE_NUMBER=256
WHITENING_DATASET="wikitext2"
SAMPLING_SEED=42
MODEL_SEQ_LEN=2048
WHITENING_INFO_SAVING_PATH="."
python SVDLLM.py
--step 1
--ratio $COMPRESSION_RATIO
--model $HUGGINGFACE_MODEL_REPO
--whitening_nsamples $WHITENING_SAMPLE_NUMBER
--dataset $WHITENING_DATASET
--seed $SAMPLING_SEED
--model_seq_len $MODEL_SEQ_LEN
--save_path $WHITENING_INFO_SAVING_PATH
--DEV cuda:3
python SVDLLM.py --step 4 \ --MODEL_PATH
And i can not run with "low-resource" mode either
The text was updated successfully, but these errors were encountered: