Create app.py

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Specify the model name from Hugging Face Hub
+model_name = "openbmb/MiniCPM-V"
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def generate_text(prompt):
+    # Tokenize the input prompt
+    inputs = tokenizer(prompt, return_tensors="pt")
+    # Generate output tokens
+    outputs = model.generate(**inputs, max_new_tokens=50)
+    # Decode tokens to text
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create a simple Gradio interface
+iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="MiniCPM-V Demo")
+iface.launch()