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README.md
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@@ -29,7 +29,11 @@ model = joblib.load(cached_download(
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# model is a `sklearn.pipeline.Pipeline`
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data_file = cached_download(
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hf_hub_url(REPO_ID, "winequality-red.csv")
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)
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X = winedf.drop(["quality"], axis=1)
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Y = winedf["quality"]
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labels = model.predict(X[:3])
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```
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^^ get your prediction
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#### Eval
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```python
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))
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# model is a `sklearn.pipeline.Pipeline`
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```
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#### Get sample data from this repo
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```python
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data_file = cached_download(
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hf_hub_url(REPO_ID, "winequality-red.csv")
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)
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X = winedf.drop(["quality"], axis=1)
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Y = winedf["quality"]
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print(X[:3])
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```
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| | fixed acidity | volatile acidity | citric acid | residual sugar | chlorides | free sulfur dioxide | total sulfur dioxide | density | pH | sulphates | alcohol |
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|---:|----------------:|-------------------:|--------------:|-----------------:|------------:|----------------------:|-----------------------:|----------:|-----:|------------:|----------:|
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| 0 | 7.4 | 0.7 | 0 | 1.9 | 0.076 | 11 | 34 | 0.9978 | 3.51 | 0.56 | 9.4 |
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| 1 | 7.8 | 0.88 | 0 | 2.6 | 0.098 | 25 | 67 | 0.9968 | 3.2 | 0.68 | 9.8 |
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| 2 | 7.8 | 0.76 | 0.04 | 2.3 | 0.092 | 15 | 54 | 0.997 | 3.26 | 0.65 | 9.8 |
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#### Get your prediction
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```python
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labels = model.predict(X[:3])
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# [5, 5, 5]
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```
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#### Eval
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```python
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