new file: requirements.txt

Dockerfile

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+# please visit https://github.com/xfyun/aiges/releases to get stable and suitable iamges.
+
+FROM iflyopensource/aiges-gpu:11.2-1.17-3.9.13-ubuntu1804-v3.3.2
+RUN sed -i 's@//.*archive.ubuntu.com@//mirrors.ustc.edu.cn@g' /etc/apt/sources.list
+RUN sed -i 's/security.ubuntu.com/mirrors.ustc.edu.cn/g' /etc/apt/sources.list
+
+RUN --mount=target=/root/packages.txt,source=packages.txt  apt-get update && xargs -r -a /root/packages.txt apt-get install -y && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /home/user/app
+RUN useradd -m -u 1000 user
+RUN chown  -R 1000.1000 /home/user
+
+
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+RUN apt-get install git-lfs
+RUN git lfs install
+RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple/
+
+
+RUN pip install --no-cache-dir pip==22.3.1
+RUN --mount=target=requirements.txt,source=requirements.txt 	pip install --no-cache-dir -r requirements.txt
+
+COPY --chown=1000 ./ /home/user/app
+
+RUN git clone http://172.16.59.16:3000/Seethal/sentiment_analysis_generic_dataset.git
+
+CMD ["python3", "app.py"]

app.py

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+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoConfig, AutoModelForSequenceClassification
+
+modelName="sentiment_analysis_generic_dataset"
+
+tokenizer = AutoTokenizer.from_pretrained(modelName)
+#model = AutoModelForSequenceClassification.from_pretrained(modelName)
+sentimentPipeline = pipeline("sentiment-analysis", model=modelName, tokenizer=tokenizer)
+Label2Des = {
+    "LABEL_0": "NEGATIVE",
+    "LABEL_1": "NEUTRAL",
+    "LABEL_2": "POSITIVE"
+}
+
+def sentiment_analysis(text):
+    results = sentimentPipeline(text)
+
+    return f"Sentiment: {Label2Des.get(results[0]['label'])}, Score: {results[0]['score']:.2f}" 
+    
+demo = gr.Interface(fn=sentiment_analysis, 
+                    inputs='text', 
+                    outputs='text',
+                    title = "文本情感分析"
+                    )
+
+
+if __name__ == "__main__":
+    demo.queue(concurrency_count=3)
+    demo.launch(server_name = "0.0.0.0")

packages.txt

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+git
+curl

requirements.txt

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+gradio==3.21.0
+transformers==4.27.1
+torch==2.0.0
+timm