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README.md
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@@ -6,15 +6,18 @@ language:
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- ko
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- en
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pipeline_tag: translation
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---
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사용 데이터셋:
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훈련 환경:
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epoch: 1
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time:
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``` python
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import torch
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@@ -22,7 +25,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
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from peft import prepare_model_for_kbit_training, PeftModel, PeftConfig
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model_path = 'yanolja/EEVE-Korean-Instruct-10.8B-v1.0'
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lora_path = 'qwopqwop/EEVE-ALMA'
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bnb_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_compute_dtype=torch.float16,)
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model = AutoModelForCausalLM.from_pretrained(model_path, quantization_config=bnb_config, trust_remote_code=True)
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- ko
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- en
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pipeline_tag: translation
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datasets:
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- qwopqwop/ALMA-R-ko-en
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---
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원본 peft모델: qwopqwop/ALMA-EEVE-v1
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사용 데이터셋: qwopqwop/ALMA-R-ko-en
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훈련 환경: A6000
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epoch: 1
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time: 1시간
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``` python
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import torch
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from peft import prepare_model_for_kbit_training, PeftModel, PeftConfig
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model_path = 'yanolja/EEVE-Korean-Instruct-10.8B-v1.0'
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lora_path = 'qwopqwop/EEVE-ALMA-R'
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bnb_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_compute_dtype=torch.float16,)
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model = AutoModelForCausalLM.from_pretrained(model_path, quantization_config=bnb_config, trust_remote_code=True)
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