Update app.py
Browse files
app.py
CHANGED
@@ -45,19 +45,46 @@ os.makedirs(app.config['MODEL_FOLDER'], exist_ok=True)
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# prediction analysis
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# Download the model file to the specified location
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repo_id="WebashalarForML/Diamond_model_",
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filename="models_list/
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cache_dir=
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)
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with open(
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# classifcation analysis
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col_model = load(os.path.join(MODEL_DIR, 'classification_LogisticRegression_col.joblib'))
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# prediction analysis
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# Download the model file to the specified location
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file_path_1 = hf_hub_download(
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repo_id="WebashalarForML/Diamond_model_",
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filename="models_list/mkble/StackingRegressor_best_pipeline_mkble_0_to_1.01.pkl",
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cache_dir=MODEL_FOLDER
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)
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with open(file_path_1, "rb") as f:
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makable_model = pickle.load(f)
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file_path_2 = hf_hub_download(
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repo_id="WebashalarForML/Diamond_model_",
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filename="models_list/grd/StackingRegressor_best_pipeline_grd_0_to_1.01.pkl",
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cache_dir=MODEL_FOLDER
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)
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with open(file_path_2, "rb") as f:
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grade_model = pickle.load(f)
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file_path_3 = hf_hub_download(
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repo_id="WebashalarForML/Diamond_model_",
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filename="models_list/bygrad/StackingRegressor_best_pipeline_bygrad_0_to_1.01.pkl",
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cache_dir=MODEL_FOLDER
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)
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with open(file_path_3, "rb") as f:
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bygrade_model = pickle.load(f)
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file_path_4 = hf_hub_download(
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repo_id="WebashalarForML/Diamond_model_",
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filename="models_list/gia/StackingRegressor_best_pipeline_gia_0_to_1.01.pkl",
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cache_dir=MODEL_FOLDER
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)
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with open(file_path_4, "rb") as f:
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gia_model = pickle.load(f)
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#gia_model = load(os.path.join(MODEL_DIR, 'linear_regression_model_gia_price.joblib'))
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#grade_model = load(os.path.join(MODEL_DIR, 'linear_regression_model_grade_price.joblib'))
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#bygrade_model = load(os.path.join(MODEL_DIR, 'linear_regression_model_bygrade_price.joblib'))
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#makable_model = load(os.path.join(MODEL_DIR, 'linear_regression_model_makable_price.joblib'))
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# classifcation analysis
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col_model = load(os.path.join(MODEL_DIR, 'classification_LogisticRegression_col.joblib'))
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