Uploading blood request emergency text classifier demo app.py

README.md

@@ -1,14 +1,52 @@
+
 ---
-title: Blood Request Emergency Text Classifier
-emoji: 🌍
+title: Emergency Blood Request Classifier
+emoji: 🩸
 colorFrom: red
 colorTo: pink
 sdk: gradio
-sdk_version: 6.18.0
-python_version: '3.13'
+sdk_version: 5.0.0
 app_file: app.py
 pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🩸 Emergency Blood Request Classifier
+
+A simple text classification demo to detect whether a blood donation request is an **emergency** or **non-emergency**.
+
+## 🔍 How It Works
+
+Type or paste a blood request message into the text box and the model will classify it into one of two categories:
+
+- 🚨 **Emergency** — Requires immediate attention
+- ✅ **Non-Emergency** — Can be handled in a routine manner
+
+Along with the verdict, you'll also see the **probability scores** for both classes.
+
+## 🧠 Model
+
+| Detail | Info |
+|---|---|
+| Base Model | [distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) |
+| Fine-tuned Model | [AshenFdo/emergency_blood_request_classifier](https://huggingface.co/AshenFdo/emergency_blood_request_classifier) |
+| Dataset | [AshenFdo/synthetic_blood_request_urgency_dataset](https://huggingface.co/datasets/AshenFdo/synthetic_blood_request_urgency_dataset) |
+| Task | Text Classification |
+| Accuracy | 100% on eval set |
+
+## 🚀 Try It Out
+
+Just enter a message like:
+
+> *"Patient is in critical condition after surgery and urgently needs O- blood immediately."*
+
+or
+
+> *"Looking for a B+ donor for a planned surgery next month."*
+
+## 🔗 Links
+
+- 📦 [Fine-tuned Model](https://huggingface.co/AshenFdo/emergency_blood_request_classifier)
+- 📊 [Dataset](https://huggingface.co/datasets/AshenFdo/synthetic_blood_request_urgency_dataset)
+- 💻 [GitHub](https://github.com/AshenFdo/Blood-Request-Emergency-Classification-Model/blob/main/notebooks/Huggingface_blood_request_emegency_classification_model_fine_tuning_.ipynb)
+

app.py

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+
+# 1. Import the required packages
+import torch
+import gradio as gr
+
+from typing import Dict, Tuple
+from transformers import pipeline
+
+# 2. Define function to use our model on given text
+def blood_request_classifier(text: str) -> Tuple[str, Dict[str, float]]:
+    # Set up text classification pipeline
+    classifier = pipeline(
+        task="text-classification",
+        model="AshenFdo/emergency_blood_request_classifier",
+        device="cuda" if torch.cuda.is_available() else "cpu",
+        top_k=None
+    )
+
+    # Get outputs from pipeline
+    outputs = classifier(text)[0]
+
+    # Build probability scores dict + find top prediction
+    prob_scores = {}
+    top_label = ""
+    top_score = 0.0
+
+    for item in outputs:
+        label = "🚨 Emergency" if item["label"] == "LABEL_1" else "✅ Non-Emergency"
+        prob_scores[label] = round(item["score"], 4)
+        if item["score"] > top_score:
+            top_score = item["score"]
+            top_label = label
+
+    # Build a nice verdict string
+    verdict = f"{top_label}  —  Confidence: {round(top_score * 100, 2)}%"
+
+    return verdict, prob_scores
+
+# 3. Create a Gradio interface
+description = """
+A text classifier to determine whether a blood donation request is an **emergency** or **non-emergency**.
+
+Fine-tuned from [DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) on a 
+[synthetic blood request urgency dataset](https://huggingface.co/datasets/AshenFdo/synthetic_blood_request_urgency_dataset).
+
+See [source code on GitHub](https://github.com/AshenFdo/Blood-Request-Emergency-Classification-Model).
+"""
+
+demo = gr.Interface(
+    fn=blood_request_classifier,
+    inputs=gr.Textbox(
+        lines=4,
+        placeholder="Enter a blood request message here...",
+        label="Blood Request Text"
+    ),
+    outputs=[
+        gr.Textbox(label="🏷️ Verdict"),          # Shows label + confidence %
+        gr.Label(num_top_classes=2, label="📊 Probability Scores")   # Shows both class probs
+    ],
+    title="🩸 Emergency Blood Request Classifier",
+    description=description,
+    examples=[
+        ["Patient is in critical condition after surgery and urgently needs O- blood immediately or they may not survive."],
+        ["Hi, I am looking for a B+ blood donor for my father's scheduled knee replacement surgery next month."],
+        ["URGENT: Accident victim in ER needs AB+ blood NOW. Lives at stake, please respond immediately!"],
+        ["Our hospital is planning a blood donation camp next Saturday. All blood types welcome."],
+        ["A newborn baby in the ICU critically needs O+ blood within the next hour. Please help!"],
+    ],
+    theme=gr.themes.Soft(),
+    allow_flagging="never"
+)
+
+# 4. Launch the interface
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+torch
+transformers