Edge-LLM
[DAC 2024] EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting
파일 탐색기
최종 버전 다운로드 (.zip)- five_shot_mmlu_test.json
- five_shot_mmlu_val.json
- zero_shot_mmlu_test.json
- zero_shot_mmlu_val.json
- Edge-LLM-overview.png
- configuration.py
- edge_llama_modelling.py
- quantized_llama_modelling.py
- layer0_pruning_10samples.feather
- layer10_pruning_10samples.feather
- layer11_pruning_10samples.feather
- layer12_pruning_10samples.feather
- layer13_pruning_10samples.feather
- layer14_pruning_10samples.feather
- layer15_pruning_10samples.feather
- layer16_pruning_10samples.feather
- layer17_pruning_10samples.feather
- layer18_pruning_10samples.feather
- layer19_pruning_10samples.feather
- layer1_pruning_10samples.feather
- layer20_pruning_10samples.feather
- layer21_pruning_10samples.feather
- layer22_pruning_10samples.feather
- layer23_pruning_10samples.feather
- layer24_pruning_10samples.feather
- layer25_pruning_10samples.feather
- layer26_pruning_10samples.feather
- layer27_pruning_10samples.feather
- layer28_pruning_10samples.feather
- layer29_pruning_10samples.feather
- layer2_pruning_10samples.feather
- layer30_pruning_10samples.feather
- layer31_pruning_10samples.feather
- layer3_pruning_10samples.feather
- layer4_pruning_10samples.feather
- layer5_pruning_10samples.feather
- layer6_pruning_10samples.feather
- layer7_pruning_10samples.feather
- layer8_pruning_10samples.feather
- layer9_pruning_10samples.feather
- llama_pruning.py
- pruner.py
- pruning_schedular.py
- sparsegpt.py
- quantizedlinear.py
- quantizer.py
- edge_llm_train.sh
- layer_wise_pruning.sh
- layer_wise_pruning_quantization.sh
- layer_wise_quantization.sh
- argument_parser.py
- bnb_wrappers.py
- dataloader.py
- logger.py
- trainer_wrappers.py
- exploration.py
- main.py
- README.md
- requirements.txt
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/GATECH-EIC/Edge-LLM
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd Edge-LLM
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
// repository documentation
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