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import gradio as gr
import core as core
from style import CSS, LANG_SYMBOLS, T_SYMBOLS, TITLE
demo = gr.Blocks(css=CSS)
with demo:
gr.HTML(TITLE)
gr.Markdown(
"This is a collection of multilingual evaluation results obtained using our fork of the LM-evaluation-harness (https://github.com/OpenGPTX/lm-evaluation-harness), based on V1 of the https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard.\
Note that currently, benchmarks are available in 21 European languages (Irish, Maltese, Croatian missing).",
elem_classes="markdown-text",
)
selected_tab = gr.State(value=0)
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem(
"🏅 LLM accuracy benchmark",
elem_id="llm-benchmark-tab-table-acc",
id=0,
) as acc:
with gr.Column():
with gr.Row():
search_bar = gr.Textbox(
label="Search models",
placeholder=" 🔍 Separate multiple queries with ';' and press ENTER...",
show_label=True,
elem_id="search-bar",
)
model_types = gr.CheckboxGroup(
label="Select model type",
choices=[
(
f"Pretrained {T_SYMBOLS['pretrained']}",
T_SYMBOLS["pretrained"],
),
(f"Chat {T_SYMBOLS['chat']}", T_SYMBOLS["chat"]),
],
value=list(T_SYMBOLS.values()),
)
with gr.Row():
langs_bar = gr.CheckboxGroup(
choices=[(LANG_SYMBOLS.get(l, l), l) for l in core.languages_list],
value=core.languages_list,
label="Select languages to average over",
elem_id="column-select",
interactive=True,
scale=6,
)
with gr.Column(scale=1):
clear = gr.ClearButton(
langs_bar,
value="Deselect all languages",
size="sm",
scale=1,
)
select = gr.Button(
value="Select all languages",
size="sm",
scale=1,
)
select.click(
lambda: gr.CheckboxGroup(value=core.languages_list),
inputs=[],
outputs=langs_bar,
)
with gr.Row():
shown_tasks = gr.CheckboxGroup(
choices=core.get_available_task_groups(core.get_selected_task_type(0), True),
value=core.get_available_task_groups(core.get_selected_task_type(0), True),
label="Select tasks to show",
elem_id="column-select",
interactive=True,
scale=50,
)
clear = gr.ClearButton(
shown_tasks,
value="Deselect all tasks",
size="sm",
scale=1,
)
select = gr.Button(
value="Select all tasks",
size="sm",
scale=1,
)
select.click(
lambda: gr.CheckboxGroup(value=core.get_available_task_groups(core.get_selected_task_type(0), True)),
inputs=[],
outputs=shown_tasks,
)
leaderboard_table = gr.Dataframe()
with gr.TabItem(
"🌐 LLM translation benchmark",
elem_id="llm-benchmark-tab-table-misc",
id=1,
) as misc:
with gr.Column():
with gr.Row():
search_bar_misc = gr.Textbox(
label="Search models",
placeholder=" 🔍 Separate multiple queries with ';' and press ENTER...",
show_label=True,
elem_id="search-bar",
)
model_types_misc = gr.CheckboxGroup(
label="Select model type",
choices=[
(
f"Pretrained {T_SYMBOLS['pretrained']}",
T_SYMBOLS["pretrained"],
),
(f"Chat {T_SYMBOLS['chat']}", T_SYMBOLS["chat"]),
],
value=list(T_SYMBOLS.values()),
)
with gr.Row():
langs_bar_misc = gr.CheckboxGroup(
choices=[(LANG_SYMBOLS.get(l, l), l) for l in core.languages_list],
value=core.languages_list,
label="Select languages to average over",
elem_id="column-select",
interactive=True,
scale=6,
)
with gr.Column(scale=1):
clear_misc = gr.ClearButton(
langs_bar_misc,
value="Deselect all languages",
size="sm",
scale=1,
)
select_misc = gr.Button(
value="Select all languages",
size="sm",
scale=1,
)
select_misc.click(
lambda: gr.CheckboxGroup(value=core.languages_list),
inputs=[],
outputs=langs_bar_misc,
)
with gr.Row():
shown_tasks_misc = gr.CheckboxGroup(
choices=core.get_available_task_groups(core.get_selected_task_type(1), False),
value=core.get_available_task_groups(core.get_selected_task_type(1), False),
label="Select tasks to show",
elem_id="column-select",
interactive=True,
scale=50,
)
clear_tasks_misc = gr.ClearButton(
shown_tasks_misc,
value="Deselect all tasks",
size="sm",
scale=1,
)
select_all_tasks_misc = gr.Button(
value="Select all tasks",
size="sm",
scale=1,
)
select_all_tasks_misc.click(
lambda: gr.CheckboxGroup(value=core.get_available_task_groups(core.get_selected_task_type(1), False)),
inputs=[],
outputs=shown_tasks_misc,
)
leaderboard_table_misc = gr.Dataframe()
for comp, fn in [
(search_bar, "submit"),
(langs_bar, "change"),
(shown_tasks, "change"),
(model_types, "change"),
]:
getattr(comp, fn)(
core.update_df,
[shown_tasks, search_bar, langs_bar, model_types, gr.State(value=True)],
leaderboard_table,
)
for comp, fn in [
(search_bar_misc, "submit"),
(langs_bar_misc, "change"),
(shown_tasks_misc, "change"),
(model_types_misc, "change"),
]:
getattr(comp, fn)(
core.update_df,
[shown_tasks_misc, search_bar_misc, langs_bar_misc, model_types_misc, gr.State(value=False)],
leaderboard_table_misc,
)
gr.Blocks.load(
block=demo,
fn=core.update_df,
inputs=[shown_tasks, search_bar, langs_bar, model_types, gr.State(value=True)],
outputs=leaderboard_table,
)
gr.Blocks.load(
block=demo,
fn=core.update_df,
inputs=[shown_tasks_misc, search_bar_misc, langs_bar_misc, model_types_misc, gr.State(value=False)],
outputs=leaderboard_table_misc,
)
demo.launch()
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