codeparrot/codeparrot-subspace
9
1import gradio as gr2from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed, pipeline3 4#https://huggingface.co/spaces/lvwerra/codeparrot-generation5 6title = "CodeParrot Generator 🦜"7description = "This is a subspace to make code generation with [CodeParrot](https://huggingface.co/lvwerra/codeparrot), it is used in a larger [space](https://huggingface.co/spaces/loubnabnl/Code-generation-models-v1) for model comparison. For more flexibilty in sampling, you can find another demo for CodeParrot [here](https://huggingface.co/spaces/lvwerra/codeparrot-generation)."8example = [9 ["def print_hello_world():", 8, 0.6, 42],10 ["def get_file_size(filepath):", 40, 0.6, 42],11 ["def count_lines(filename):", 40, 0.6, 42],12 ["def count_words(filename):", 40, 0.6, 42]]13tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot")14model = AutoModelForCausalLM.from_pretrained("codeparrot/codeparrot", low_cpu_mem_usage=True)15 16 17def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):18 set_seed(seed)19 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)20 generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']21 return generated_text22 23 24iface = gr.Interface(25 fn=code_generation, 26 inputs=[27 gr.Textbox(lines=10, label="Input code"),28 gr.inputs.Slider(29 minimum=8,30 maximum=256,31 step=1,32 default=8,33 label="Number of tokens to generate",34 ),35 gr.inputs.Slider(36 minimum=0,37 maximum=2,38 step=0.1,39 default=0.6,40 label="Temperature",41 ),42 gr.inputs.Slider(43 minimum=0,44 maximum=1000,45 step=1,46 default=42,47 label="Random seed to use for the generation"48 )49 ],50 outputs=gr.Textbox(label="Predicted code", lines=10),51 examples=example,52 layout="horizontal",53 theme="peach",54 description=description,55 title=title56)57iface.launch()