Spaces:
Runtime error
Runtime error
import json | |
import os | |
import shutil | |
import requests | |
import gradio as gr | |
from huggingface_hub import Repository | |
from text_generation import Client | |
from share_btn import community_icon_html, loading_icon_html, share_js, share_btn_css | |
HF_TOKEN = os.environ.get("HF_TOKEN", None) | |
API_URL = "https://api-inference.huggingface.co/models/codellama/CodeLlama-7b-hf" | |
FIM_PREFIX = "<PRE> " | |
FIM_MIDDLE = " <MID>" | |
FIM_SUFFIX = " <SUF>" | |
FIM_INDICATOR = "<FILL_ME>" | |
EOS_STRING = "</s>" | |
EOT_STRING = "<EOT>" | |
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( | |
prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, | |
): | |
temperature = float(temperature) | |
if temperature < 1e-2: | |
temperature = 1e-2 | |
top_p = float(top_p) | |
fim_mode = False | |
generate_kwargs = dict( | |
temperature=temperature, | |
max_new_tokens=max_new_tokens, | |
top_p=top_p, | |
repetition_penalty=repetition_penalty, | |
do_sample=True, | |
seed=42, | |
) | |
if FIM_INDICATOR in prompt: | |
fim_mode = True | |
try: | |
prefix, suffix = prompt.split(FIM_INDICATOR) | |
except: | |
raise ValueError(f"Only one {FIM_INDICATOR} allowed in prompt!") | |
prompt = f"{FIM_PREFIX}{prefix}{FIM_SUFFIX}{suffix}{FIM_MIDDLE}" | |
stream = client.generate_stream(prompt, **generate_kwargs) | |
if fim_mode: | |
output = prefix | |
else: | |
output = prompt | |
previous_token = "" | |
for response in stream: | |
if any([end_token in response.token.text for end_token in [EOS_STRING, EOT_STRING]]): | |
if fim_mode: | |
output += suffix | |
yield output | |
return output | |
print("output", output) | |
else: | |
return output | |
else: | |
output += response.token.text | |
previous_token = response.token.text | |
yield output | |
return output | |
examples = [ | |
"X_train, y_train, X_test, y_test = train_test_split(X, y, test_size=0.1)\n\n# Train a logistic regression model, predict the labels on the test set and compute the accuracy score", | |
"// Returns every other value in the array as a new array.\nfunction everyOther(arr) {", | |
"Poor English: She no went to the market. Corrected English:", | |
"def alternating(list1, list2):\n results = []\n for i in range(min(len(list1), len(list2))):\n results.append(list1[i])\n results.append(list2[i])\n if len(list1) > len(list2):\n <FILL_HERE>\n else:\n results.extend(list2[i+1:])\n return results", | |
"def remove_non_ascii(s: str) -> str:\n \"\"\" <FILL_ME>\nprint(remove_non_ascii('afkdj$$('))", | |
] | |
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; | |
} | |
""" | |
css += share_btn_css + monospace_css + ".gradio-container {color: black}" | |
description = """ | |
<div style="text-align: center;"> | |
<h1> 🦙 Code Llama Playground</h1> | |
</div> | |
<div style="text-align: left;"> | |
<p>This is a demo to generate text and code with the following <a href="https://huggingface.co/codellama/CodeLlama-13b-hf">Code Llama model (13B)</a>. Please note that this model is not designed for instruction purposes but for code completion. If you're looking for instruction or want to chat with a fine-tuned model, you can use [this demo instead](https://huggingface.co/spaces/codellama/codellama-13b-chat). You can learn more about the model in the <a href="https://huggingface.co/blog/codellama/">blog post<\a> or <a href="https://huggingface.co/papers/2308.12950">paper<\a></p> | |
</div> | |
""" | |
with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo: | |
with gr.Column(): | |
gr.Markdown(description) | |
with gr.Row(): | |
with gr.Column(): | |
instruction = gr.Textbox( | |
placeholder="Enter your code 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") | |
with gr.Row(): | |
with gr.Column(): | |
with gr.Accordion("Advanced settings", open=False): | |
with gr.Row(): | |
column_1, column_2 = gr.Column(), gr.Column() | |
with column_1: | |
temperature = gr.Slider( | |
label="Temperature", | |
value=0.1, | |
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=1.05, | |
minimum=1.0, | |
maximum=2.0, | |
step=0.05, | |
interactive=True, | |
info="Penalize repeated tokens", | |
) | |
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) |