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澶фā鍨嬶紙LLMs錛夊弬鏁伴珮鏁堝井璋?PEFT) 闈?PDF 涓嬭澆

杞澆鑷細http://www.python222.com/article/1191

鐩稿叧鎴浘錛?/strong>

涓昏鍐呭錛?/strong>

1. 寰皟鏂規(guī)硶鏄暐錛熷浣曞井璋冿紵

fine-tune錛屼篃鍙叏鍙傚井璋冿紝bert寰皟妯″瀷涓€鐩寸敤鐨勮繖縐嶆柟娉曪紝鍏ㄩ儴鍙傛暟鏉冮噸鍙備笌鏇存柊浠ラ€傞厤棰嗗煙鏁版嵁錛屾晥鏋滃ソ銆?/span>

prompt-tune, 鍖呮嫭p-tuning銆?/span>lora銆?/span>prompt-tuning銆?/span>adaLoRA絳?/span>delta tuning鏂規(guī)硶錛岄儴鍒嗘ā鍨嬪弬鏁板弬涓庡井璋冿紝璁粌

蹇紝鏄懼瓨鍗犵敤灝戯紝鏁堟灉鍙兘璺?/span>FT錛?/span>fine-tune錛夋瘮浼氱◢鏈夋晥鏋滄崯澶憋紝浣嗕竴鑸晥鏋滆兘鎵撳鉤銆?/span>

閾懼鍦?/span>BELLE鐨勬妧鏈姤鍛娿€?/span>A Comparative Study between Full-Parameter and LoRA-based Fine-Tuning on

Chinese Instruction Data for Instruction Following Large Language Model銆嬩腑瀹為獙鏄劇ず錛?/span>FT鏁堟灉紼嶅ソ浜?/span>LoRA銆?/span>

2. 涓轟粈涔堥渶瑕?/strong> PEFT錛?/strong>

鍦ㄩ潰瀵圭壒瀹氱殑涓嬫父浠誨姟鏃訛紝濡傛灉榪涜Full FineTuning錛堝嵆瀵歸璁粌妯″瀷涓殑鎵€鏈夊弬鏁伴兘榪涜寰皟錛夛紝澶繃浣庢晥錛?/span>

鑰屽鏋滈噰鐢ㄥ浐瀹氶璁粌妯″瀷鐨勬煇浜涘眰錛屽彧寰皟鎺ヨ繎涓嬫父浠誨姟鐨勯偅鍑犲眰鍙傛暟錛屽張闅句互杈懼埌杈冨ソ鐨勬晥鏋溿€?/span>

3. 浠嬬粛涓€涓?/strong> PEFT錛?/strong>

PEFT鎶€鏈棬鍦?/span>閫氳繃鏈€灝忓寲寰皟鍙傛暟鐨勬暟閲忓拰璁＄畻澶嶆潅搴︼紝鏉ユ彁楂橀璁粌妯″瀷鍦ㄦ柊浠誨姟涓婄殑鎬ц兘錛屼粠鑰岀紦瑙ｅぇ鍨?/strong>

棰勮緇冩ā鍨嬬殑璁粌鎴愭湰銆傝繖鏍蜂竴鏉ワ紝鍗充嬌璁＄畻璧勬簮鍙楅檺錛屼篃鍙互鍒╃敤棰勮緇冩ā鍨嬬殑鐭ヨ瘑鏉ヨ繀閫熼€傚簲鏂頒換鍔★紝瀹炵幇

楂樻晥鐨勮縼縐誨涔犮€?/span>

4. PEFT 鏈変粈涔堜紭鐐癸紵

PEFT鎶€鏈彲浠ュ湪鎻愰珮妯″瀷鏁堟灉鐨勫悓鏃訛紝澶уぇ緙╃煭妯″瀷璁粌鏃墮棿鍜岃綆楁垚鏈紝璁╂洿澶氫漢鑳藉鍙備笌鍒版繁搴﹀涔犵爺絀?/span>

涓潵銆傞櫎姝や箣澶栵紝FEFT鍙互緙撹В鍏ㄩ噺寰皟甯︽潵鐏鵑毦鎬ч仐蹇樼殑闂銆?/span>

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澶фā鍨嬶紙LLMs錛夊弬鏁伴珮鏁堝井璋?PEFT) 闈?PDF 涓嬭澆

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