Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "khaled123/chess"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define the function to generate text
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=50)
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_text
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_text,
+    inputs="text",
+    outputs="text",
+    title="Chess Model based on LLaMA 2",
+    description="Type a prompt and the model will generate text based on it."
+)
+
+# Launch the interface
+iface.launch()