Comments (1)
tuidan
commented on August 20, 2024
Hi! We strongly recommend to compress llama 7B on A100. However, it is still possible to run the compression with only 20G GPU memory by the following command:
python SVDLLM.py --step 1 --run_low_resource --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
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Related Issues (11)
- Request for Code Integration of SVD-LLM with GPTQ HOT 2
- Instead of ratio-compress to specific layer size HOT 1
- Incorrect Model Responses after compression HOT 4
- fail to apply on llama-13b HOT 2
- still fail to apply on llama-13b HOT 2
- compresssed checkpoints HOT 1
- Compressed Model Produces Random and Repetitive Output - Request for Compressed Weights HOT 1
- Question about C4 dataset HOT 4
- Question about ASVD and FWSVD HOT 1
- Converting Compressed LLaMA2 Model to Hugging Face-Compatible Format HOT 1
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