import os import gradio as gr from text_generation import Client HF_TOKEN = os.environ.get("HF_TOKEN", None) API_URL = " https://api-inference.huggingface.co/models/BigCode/octocoder" theme = gr.themes.Monochrome( primary_hue="indigo", secondary_hue="blue", neutral_hue="slate", radius_size=gr.themes.sizes.radius_sm, font=[ gr.themes.GoogleFont("Open Sans"), "ui-sans-serif", "system-ui", "sans-serif", ], ) client = Client( API_URL, headers={"Authorization": f"Bearer {HF_TOKEN}"}, ) def generate(query:str, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ): if query.endswith("."): prompt = f"Question: {query}\n\nAnswer:" else: prompt = f"Question: {query}.\n\nAnswer:" temperature = float(temperature) if temperature < 1e-2: temperature = 1e-2 top_p = float(top_p) generate_kwargs = dict( temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetition_penalty, do_sample=True, seed=42, ) stream = client.generate_stream(prompt, **generate_kwargs) output = "" previous_token = "" for response in stream: if response.token.text == "<|endoftext|>": return output else: output += response.token.text previous_token = response.token.text yield output return output def process_example(args): for x in generate(args): pass return x css = ".generating {visibility: hidden}" monospace_css = """ #q-input textarea { font-family: monospace, 'Consolas', Courier, monospace; } """ description = """

OctoCoder Demo


This is a demo to demonstrate the capabilities of OctoCoder model by showing how it can be used to generate code by following the instructions provided in the input.

OctoCoder is an instruction tuned model with 15.5B parameters created by finetuning StarCoder on CommitPackFT & OASST

""" disclaimer = """⚠️Any use or sharing of this demo constitues your acceptance of the BigCode [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) License Agreement and the use restrictions included within.\
**Intended Use**: this app and its [supporting model](https://huggingface.co/bigcode) are provided for demonstration purposes; not to serve as replacement for human expertise. For more details on the model's limitations in terms of factuality and biases, see the [model card.](https://huggingface.co/bigcode)""" examples = [['Please write a function in Python that performs bubble sort.']] with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo: with gr.Column(): gr.Markdown(description) with gr.Row(): with gr.Column(): with gr.Accordion("Settings", open=True): with gr.Row(): column_1, column_2 = gr.Column(), gr.Column() with column_1: temperature = gr.Slider( label="Temperature", value=0.2, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs", ) max_new_tokens = gr.Slider( label="Max new tokens", value=256, minimum=0, maximum=8192, step=64, interactive=True, info="The maximum numbers of new tokens", ) with column_2: top_p = gr.Slider( label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens", ) repetition_penalty = gr.Slider( label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens", ) with gr.Row(): with gr.Column(): instruction = gr.Textbox( placeholder="Enter your query here", lines=5, label="Input", elem_id="q-input", ) submit = gr.Button("Generate", variant="primary") output = gr.Code(elem_id="q-output", lines=30, label="Output") gr.Markdown(disclaimer) gr.Examples( examples=examples, inputs=[instruction], cache_examples=False, fn=process_example, outputs=[output], ) submit.click( generate, inputs=[instruction, temperature, max_new_tokens, top_p, repetition_penalty], outputs=[output], ) demo.queue(concurrency_count=16).launch(debug=True)