AnasHXH/ROS2

1import gradio as gr2from transformers import AutoTokenizer, AutoModelForSeq2SeqLM3 4# Load your model5model_checkpoint = "AnasHXH/Ros_model"6tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)7model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)8 9def generate_command(input_text):10    # Tokenize text and convert to model input format11    inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)12    # Generate output from the model13    outputs = model.generate(inputs["input_ids"])14    # Decode the generated tokens to text15    command = tokenizer.decode(outputs[0], skip_special_tokens=True)16    return command17 18# Define your Gradio interface19iface = gr.Interface(20    fn=generate_command,  # the function to wrap21    inputs="text",        # the input data type22    outputs="text",       # the output data type23    title="Robot Command Generator",24    description="Type in English to get the robot command"25)26 27# Run the Gradio app28iface.launch()