# import spaces
# import transformers
# import gradio as gr

# def greet(name):
#     return "Hello " + name + "!!"


# # @spaces.GPU
# # def infer(input_text: str = "Who are you?"):

# #     # messages = [
# #     #     {"role": "user", "content": name},
# #     # ]
# #     model = transformers.AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct", trust_remote_code=True)
# #     token = transformers.AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct", trust_remote_code=True)
# #     input_ids = token.encode(input_text, return_tensors="pt" )
# #     output = model(input_ids)
# #     print(output)
# #     return output

# @spaces.GPU
# def infer_demo(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):

# text_input = gr.Textbox(label="Input Text", placeholder="test")

# demo = gr.Interface(fn=infer, inputs="text", outputs="text")
# demo.launch()