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app.py

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+import numpy as np
+import pickle
+import gradio as gr
+from huggingface_hub import hf_hub_download
+
+# Load model and scaler from Hugging Face Hub
+model_path = hf_hub_download(repo_id="nitinnyadavvv/cricpred", filename="xgb_model.pkl")
+scaler_path = hf_hub_download(repo_id="nitinnyadavvv/cricpred", filename="scaler.pkl")
+
+model = pickle.load(open(model_path, "rb"))
+scaler = pickle.load(open(scaler_path, "rb"))
+
+def predict_run(over_number, ball_number, total_runs_till_now, total_wickets, current_run_rate,
+                last_3_balls_runs, last_over_runs, partnership_runs, current_over_score):
+    # Create input array
+    features = np.array([[over_number, ball_number, total_runs_till_now, total_wickets,
+                         current_run_rate, last_3_balls_runs, last_over_runs,
+                         partnership_runs, current_over_score]])
+    
+    # Scale features
+    scaled_features = scaler.transform(features)
+    
+    # Make prediction
+    prediction = model.predict(scaled_features)
+    
+    # Return rounded prediction
+    return round(float(prediction[0]), 2)
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Cricket Run Predictor")
+    gr.Markdown("Predict runs scored in the current over using match context.")
+    
+    with gr.Row():
+        with gr.Column():
+            over_number = gr.Number(label="Over Number (0-50)", value=10)
+            ball_number = gr.Number(label="Ball Number (1-6)", value=3)
+            total_runs_till_now = gr.Number(label="Total Runs Till Now", value=80)
+            total_wickets = gr.Number(label="Total Wickets (0-10)", value=2)
+            current_run_rate = gr.Number(label="Current Run Rate", value=5.5)
+        with gr.Column():
+            last_3_balls_runs = gr.Number(label="Last 3 Balls Runs", value=6)
+            last_over_runs = gr.Number(label="Last Over Runs", value=9)
+            partnership_runs = gr.Number(label="Partnership Runs", value=45)
+            current_over_score = gr.Number(label="Current Over Score", value=8)
+    
+    predict_btn = gr.Button("Predict Runs")
+    output = gr.Number(label="Predicted Runs in This Over")
+    
+    predict_btn.click(
+        fn=predict_run,
+        inputs=[over_number, ball_number, total_runs_till_now, total_wickets,
+                current_run_rate, last_3_balls_runs, last_over_runs,
+                partnership_runs, current_over_score],
+        outputs=output
+    )
+
+demo.launch()

requirements.txt

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+gradio>=3.0
+numpy
+scikit-learn
+xgboost
+huggingface-hub

scaler.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4a5da4e3bf9d0cc512cf288db42ea5b3363cc14d16e37d77be277e78dcd48919
+size 913

xgb_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9fcde55d867fd98e85728d1f33c1eae894a18d89c6f8174d45eccfe4cab2bd8f
+size 1406291