Add application file

app.py

@@ -0,0 +1,84 @@
+"""
+This module provides an interface for summarizing medical text using FALCONS.AI's medical_summarization model.
+The interface allows users to enter text from a medical document.
+The user will receive a generated summary of the medical text.
+"""
+
+import gradio as gr
+import spaces
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Set device
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Load tokenizer with fast processing enabled
+tokenizer = AutoTokenizer.from_pretrained(
+    "Falconsai/medical_summarization",
+    use_fast=True
+)
+
+# Load model with bf16 for optimized memory usage
+model = AutoModelForSeq2SeqLM.from_pretrained(
+    "Falconsai/medical_summarization",
+    torch_dtype=torch.bfloat16
+)
+
+# Move model to device
+model.to(DEVICE)
+
+@spaces.GPU
+def summarize(text):
+    """
+    Generate a summary of the text from a medical document.
+
+    Args:
+        text (str): The text of a medical document.
+
+    Returns:
+        str: The generated summary of the medical text.
+    """
+    # Tokenize the text for summarization
+    tokenized_input = tokenizer(
+        text,
+        return_tensors="pt"
+    ).input_ids.to(DEVICE)
+
+    # Generate a summary prediction using the model
+    summary_ids = model.generate(
+        input_ids=tokenized_input,
+        max_new_tokens=500
+    )
+
+    # Decode the generated summary
+    summary = tokenizer.batch_decode(
+        summary_ids,
+        skip_special_tokens=True
+    )
+
+    return summary[0]
+
+TITLE = "Medical Text Summarizer"
+DESCRIPTION = """
+Summarize medical text using FALCONS.AI's medical_summarization model.
+"""
+
+# Gradio components
+input_text = gr.Textbox(
+    label="Medical document",
+    placeholder="Enter text here"
+)
+
+output_text = gr.Textbox(label="Summary")
+
+# Define the Gradio interface
+demo = gr.Interface(
+    fn=summarize,
+    inputs=[input_text],
+    outputs=[output_text],
+    title=TITLE,
+    description=DESCRIPTION
+)
+
+# Launch the Gradio interface
+demo.launch()