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2b63692
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Parent(s):
3353585
Upload 3 files
Browse files- README.md +5 -4
- app.py +51 -0
- requirements.txt +4 -0
README.md
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---
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title: Wine
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colorFrom:
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colorTo: green
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Wine
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emoji: 🐢
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colorFrom: pink
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colorTo: green
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sdk: gradio
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sdk_version: 3.5
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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from PIL import Image, ImageDraw, ImageFont
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import requests
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import hopsworks
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import joblib
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import pandas as pd
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project = hopsworks.login()
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fs = project.get_feature_store()
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mr = project.get_model_registry()
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model = mr.get_model("wine_model", version=1)
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model_dir = model.download()
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model = joblib.load(model_dir + "/wine_model.pkl")
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print("Model downloaded")
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def wine(fixed_acidity, citric_acid, type_white, chlorides, volatile_acidity, density, alcohol):
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print("Calling function")
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# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
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df = pd.DataFrame([[fixed_acidity, citric_acid, type_white, chlorides, volatile_acidity, density, alcohol]],
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columns=['fixed_acidity', 'citric_acid', 'type_white', 'chlorides', 'volatile_acidity', 'density', 'alcohol'])
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print("Predicting")
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print(df)
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# 'res' is a list of predictions returned as the label.
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res = model.predict(df)
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# We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
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# the first element.
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# print("Res: {0}").format(res)
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print(res)
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return str(res[0])
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demo = gr.Interface(
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fn=wine,
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title="Wine Quality Predictive Analytics",
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description="Experiment with fixed_acidity, citric_acid, type, chlorides, volatile_acidity, density, alcohol"
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"to predict of which quality the wine is.",
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allow_flagging="never",
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inputs=[
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gr.inputs.Number(default=7.2, label="fixed acidity"),
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gr.inputs.Number(default=0.34, label="volatile acidity"),
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gr.inputs.Number(default=0.32, label="citric acid"),
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gr.inputs.Textbox(default="red", label="type (red, white)"),
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gr.inputs.Number(default=10.5, label="alcohol"),
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gr.inputs.Number(default=0.99, label="density"),
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gr.inputs.Number(default=0.06, label="chlorides"),
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],
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outputs="text")
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demo.launch(debug=True)
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requirements.txt
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hopsworks
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joblib
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scikit-learn==1.1.1
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httpx==0.24.1
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