Add application file

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from transformers import AutoTokenizer, pipeline
+import torch
+
+# Initialize the model and tokenizer
+model = "Isaak-Carter/JOSIE_Beta-5-7B-slerp"
+tokenizer = AutoTokenizer.from_pretrained(model)
+
+ai_pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_name,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+def generate_response(user_input):
+    """
+    Generate a response to the user input using the specified AI model.
+    
+    Args:
+        user_input (str): The question or prompt from the user.
+
+    Returns:
+        str: The generated response from the AI model.
+    """
+    messages = [{"role": "user", "content": user_input}]
+    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+    pipeline = transformers.pipeline(
+        "text-generation",
+        model=model,
+        torch_dtype=torch.float16,
+        device_map="auto",
+    )
+
+    outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+
+    return outputs[0]["generated_text"]
+
+# Create Gradio interface
+interface = gr.Interface(fn=generate_response, inputs="text", outputs="text", title="JOSIE Beta 5", description="Asc JOSIE Beta 5.")
+interface.launch()
+