Initial Gradio version with GPU

app.py

@@ -1,4 +1,4 @@
-import streamlit as st
+import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import re
@@ -9,14 +9,31 @@ import io
 
 # Load model and tokenizer from local fine-tuned directory
 # Define base and adapter model paths
-BASE_MODEL = "stanford-crfm/BioMedLM"  # or the path you used originally
-ADAPTER_PATH = "Tufan1/BioMedLM-Cardio-Fold4-CPU"
-tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
-
+#BASE_MODEL = "stanford-crfm/BioMedLM"  # or the path you used originally
+#ADAPTER_PATH = "Tufan1/BioMedLM-Cardio-Fold4-CPU"
+#tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
+MODEL_PATH = "Tufan1/BioMedLM-Cardio-Fold4-CPU"
 # Force CPU-safe model loading
-base_model = AutoModelForCausalLM.from_pretrained(BASE_MODEL, torch_dtype=torch.float32)
-model = PeftModel.from_pretrained(base_model, ADAPTER_PATH, device_map=None).to("cpu")
-
+#base_model = AutoModelForCausalLM.from_pretrained(BASE_MODEL, torch_dtype=torch.float32)
+#model = PeftModel.from_pretrained(base_model, ADAPTER_PATH, device_map=None).to("cpu")
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, torch_dtype=torch.float16).to("cuda")
+
+def predict_disease(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+    outputs = model.generate(**inputs, max_new_tokens=100)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+iface = gr.Interface(
+    fn=predict_disease,
+    inputs=gr.Textbox(label="Enter Symptoms"),
+    outputs=gr.Textbox(label="Predicted Diagnosis"),
+    title="Cardiovascular Disease Predictor",
+    description="Enter patient symptoms to receive diagnosis based on BioMedLM."
+)
+
+iface.launch()
 
 # Dictionaries to decode user inputs
 gender_map = {1: "Female", 2: "Male"}

requirements.txt

@@ -11,7 +11,8 @@ huggingface-hub==0.30.1
 datasets==3.4.1
 
 # Web App
-streamlit==1.33.0
+# streamlit==1.33.0
+gradio==5.24.0
 
 # Audio Processing
 pydub==0.25.1