Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Load your model
+model_checkpoint = "AnasHXH/Ros_model"
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
+
+def generate_command(input_text):
+    # Tokenize text and convert to model input format
+    inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)
+    # Generate output from the model
+    outputs = model.generate(inputs["input_ids"])
+    # Decode the generated tokens to text
+    command = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return command
+
+# Define your Gradio interface
+iface = gr.Interface(
+    fn=generate_command,  # the function to wrap
+    inputs="text",        # the input data type
+    outputs="text",       # the output data type
+    title="Robot Command Generator",
+    description="Type in English to get the robot command"
+)
+
+# Run the Gradio app
+iface.launch()