s2337a commited on
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a9037ce
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1 Parent(s): 2cadbd6

Update app.py

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Files changed (1) hide show
  1. app.py +14 -57
app.py CHANGED
@@ -1,13 +1,14 @@
1
- # Load model directly
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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-
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- tokenizer = AutoTokenizer.from_pretrained("snunlp/KR-FinBert-SC")
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- model = AutoModelForSequenceClassification.from_pretrained("snunlp/KR-FinBert-SC")
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-
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  import os
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  import tensorflow as tf
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  from absl import logging
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  # 환경 변수 설정
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  os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # oneDNN 최적화 비활성화
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@@ -25,61 +26,17 @@ if gpus:
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  except RuntimeError as e:
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  print(f"GPU 설정 오류: {e}")
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- # TensorFlow 및 시스템 정보 확인
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- print("TensorFlow 버전:", tf.__version__)
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- print("사용 가능한 장치:", tf.config.list_physical_devices())
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-
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- import os
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- import tensorflow as tf
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-
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- # oneDNN 최적화 비활성화
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- os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
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-
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- # GPU 비활성화 (CUDA 문제 해결 시)
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- os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
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-
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- # TensorFlow GPU 메모리 설정
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- gpus = tf.config.experimental.list_physical_devices('GPU')
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- if gpus:
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- try:
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- for gpu in gpus:
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- tf.config.experimental.set_memory_growth(gpu, True)
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- print("GPU 메모리 증가 허용 설정 완료")
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- except RuntimeError as e:
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- print(f"GPU 설정 오류: {e}")
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-
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- # TensorFlow 실행 확인
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  print("TensorFlow 버전:", tf.__version__)
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  print("사용 가능한 장치:", tf.config.list_physical_devices())
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- # Base image
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- FROM python:3.10-slim
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-
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- # Install Python packages
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- RUN pip install --no-cache-dir pip==22.3.1 \
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- && pip install --no-cache-dir datasets "huggingface-hub>=0.19" \
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- "hf-transfer>=0.1.4" "protobuf<4" "click<8.1" "pydantic~=1.0"
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-
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- # Install system packages
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- RUN apt-get update && apt-get install -y \
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- git git-lfs ffmpeg libsm6 libxext6 cmake rsync libgl1-mesa-glx \
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- && rm -rf /var/lib/apt/lists/*
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-
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- # Work directory
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- WORKDIR /home/user/app
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-
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- # Copy requirements and install additional Python packages
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- COPY requirements.txt .
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- RUN pip install --no-cache-dir -r requirements.txt
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-
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- # Copy source code
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- COPY . .
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-
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- # Set default command
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- CMD ["streamlit", "run", "app.py"]
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-
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- import streamlit as st
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-
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  st.title("Hello, Streamlit!")
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  st.write("This is a sample Streamlit app.")
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+ # Hugging Face 모델 로드
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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+ import streamlit as st
 
 
 
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  import os
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  import tensorflow as tf
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  from absl import logging
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+ # Hugging Face 모델 설정
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+ tokenizer = AutoTokenizer.from_pretrained("snunlp/KR-FinBert-SC")
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+ model = AutoModelForSequenceClassification.from_pretrained("snunlp/KR-FinBert-SC")
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+
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  # 환경 변수 설정
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  os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0' # oneDNN 최적화 비활성화
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26
  except RuntimeError as e:
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  print(f"GPU 설정 오류: {e}")
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+ # TensorFlow 정보 출력
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  print("TensorFlow 버전:", tf.__version__)
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  print("사용 가능한 장치:", tf.config.list_physical_devices())
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+ # Streamlit 앱 인터페이스
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  st.title("Hello, Streamlit!")
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  st.write("This is a sample Streamlit app.")
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+ # 입력 필드 추가
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+ input_text = st.text_input("Enter some text:")
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+ if st.button("Analyze"):
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+ inputs = tokenizer(input_text, return_tensors="pt")
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+ outputs = model(**inputs)
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+ st.write("Model Output:", outputs.logits.tolist())