Create app.py

app.py

@@ -0,0 +1,31 @@
+# app.py
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import torch
+
+# Load the model and tokenizer from Hugging Face
+model_path = "Athagi/Agillm-v2"  # Model loaded from Hugging Face Hub
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path)
+
+# Create a text generation pipeline
+chatbot = pipeline("text-generation", model=model, tokenizer=tokenizer, device=0 if torch.cuda.is_available() else -1)
+
+# Function to generate response
+def chat_with_model(user_input):
+    response = chatbot(user_input, max_length=200, do_sample=True, temperature=0.7)
+    return response[0]['generated_text']
+
+# Gradio interface
+interface = gr.Interface(
+    fn=chat_with_model,  # Function to generate the response
+    inputs="text",  # Input: Text box for user input
+    outputs="text",  # Output: Generated response
+    title="Chat with Agillm-v2",  # Title of the app
+    description="Type a message and interact with the Agillm-v2 model.",
+    theme="huggingface"  # Optional: Use Hugging Face theme
+)
+
+# Launch the app
+interface.launch()