From bc1ed5a107003a4b8f3aaa76b66c7050f3924de9 Mon Sep 17 00:00:00 2001 From: jianjiang Date: Wed, 26 Apr 2023 16:02:48 +0800 Subject: [PATCH] t5 --- Dockerfile | 6 +++++- app.py | 3 ++- 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/Dockerfile b/Dockerfile index fe16e95..79a59f9 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,10 +1,14 @@ +#FROM python:3.8.13 FROM artifacts.iflytek.com/docker-private/atp/base_image_for_ailab:0.0.1 WORKDIR /app -COPY . /app +COPY requirements.txt /app RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple RUN pip install -r requirements.txt +COPY . /app + + CMD ["python", "app.py"] diff --git a/app.py b/app.py index d6379a6..207f706 100644 --- a/app.py +++ b/app.py @@ -25,7 +25,8 @@ demo = gr.Interface(fn=sentiment_analysis, outputs='text', examples=[["We describe a system called Overton, whose main design goal is to support engineers in building, monitoring, and improving production machinelearning systems. Key challenges engineers face are monitoring fine-grained quality, diagnosing errors in sophisticated applications, and handling contradictory or incomplete supervision data. Overton automates the life cycle of model construction, deployment, and monitoring by providing a set of novel high-level, declarative abstractions. Overton's vision is to shift developers to these higher-level tasks instead of lower-level machine learning tasks. In fact, using Overton, engineers can build deep-learning-based applications without writing any code in frameworks like TensorFlow. For over a year, Overton has been used in production to support multiple applications in both near-real-time applications and back-of-house processing. In that time, Overton-based applications have answered billions of queries in multiple languages and processed trillions of records reducing errors 1.7-2.9 times versus production systems."]], theme = theme, - title = "摘要" + css = "footer {visibility: hidden}", + allow_flagging = "never", )