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I simply use the following commands to run: python hf_prune.py --pruning_ratio 0.62785 --block_wise --block_mlp_layer_start 0 --block_mlp_layer_end 32 --block_attention_layer_start 32 --block_attention_layer_end 32 --pruner_type taylor --base_model /mnt/petrelfs/xxx/llama2-7b --device cpu --eval_device cuda --taylor param_first --save_ckpt_log_name llama_prune --save_model --num_examples 128 python hf_prune.py --pruning_ratio 0.62785 --block_wise --block_mlp_layer_start 0 --block_mlp_layer_end 32 --block_attention_layer_start 32 --block_attention_layer_end 32 --pruner_type taylor --base_model /mnt/petrelfs/xxx/llama2-7b --device cpu --eval_device cuda --taylor param_mix --save_ckpt_log_name llama_prune --save_model --num_examples 128
But they result in the same ppl.
The text was updated successfully, but these errors were encountered:
I simply use the following commands to run:
python hf_prune.py --pruning_ratio 0.62785 --block_wise --block_mlp_layer_start 0 --block_mlp_layer_end 32 --block_attention_layer_start 32 --block_attention_layer_end 32 --pruner_type taylor --base_model /mnt/petrelfs/xxx/llama2-7b --device cpu --eval_device cuda --taylor param_first --save_ckpt_log_name llama_prune --save_model --num_examples 128
python hf_prune.py --pruning_ratio 0.62785 --block_wise --block_mlp_layer_start 0 --block_mlp_layer_end 32 --block_attention_layer_start 32 --block_attention_layer_end 32 --pruner_type taylor --base_model /mnt/petrelfs/xxx/llama2-7b --device cpu --eval_device cuda --taylor param_mix --save_ckpt_log_name llama_prune --save_model --num_examples 128
But they result in the same ppl.
The text was updated successfully, but these errors were encountered: