Update app.py

app.py

@@ -1,4 +1,5 @@
-# Import necessary libraries
+import gradio as gr
+import torch
 from transformers import AutoModel, AutoTokenizer
 
 # Load the model and tokenizer
@@ -6,13 +7,26 @@ model_name = "Rafay17/Llama3.2_1b_customModle2"
 model = AutoModel.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-# Prepare your input text
-input_text = "Your input text goes here."
-inputs = tokenizer(input_text, return_tensors="pt")
+# Define a function to process input text
+def generate_output(input_text):
+    # Tokenize the input text
+    inputs = tokenizer(input_text, return_tensors="pt")
+    
+    # Forward pass to get model outputs
+    with torch.no_grad():
+        outputs = model(**inputs)
+    
+    # You can return the outputs as needed; here, we're returning the last hidden state
+    return outputs.last_hidden_state
 
-# Forward pass to get model outputs
-with torch.no_grad():
-    outputs = model(**inputs)
+# Create Gradio interface
+iface = gr.Interface(
+    fn=generate_output,
+    inputs=gr.Textbox(label="Input Text"),
+    outputs=gr.Textbox(label="Model Output"),
+    title="Text Processing with Llama Model",
+    description="Enter text to process it with the Llama3.2 model."
+)
 
-# Do something with the outputs
-print(outputs)
+# Launch the app
+iface.launch()