Create app.py

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import safetensors.torch
+
+# Load base model and tokenizer
+base_model_name = "AIDC-AI/Marco-o1"
+tokenizer = AutoTokenizer.from_pretrained(base_model_name)
+model = AutoModelForCausalLM.from_pretrained(base_model_name)
+
+# Load your lightweight safetensor
+safetensor_path = "adapter_model.safetensors"
+model.load_state_dict(safetensors.torch.load_file(safetensor_path), strict=False)
+
+def predict(text):
+    inputs = tokenizer.encode(text, return_tensors="pt")
+    outputs = model.generate(inputs)
+    prediction = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return prediction
+
+demo = gr.Interface(fn=predict, inputs="text", outputs="text")
+demo.launch()