Spaces:
Running
Running
File size: 3,406 Bytes
df32536 7036416 df32536 da544b6 df32536 bc0f422 df32536 bc0f422 df32536 65684de df32536 65684de df32536 bc0f422 df32536 bc0f422 df32536 7036416 bc0f422 df32536 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 |
import gradio as gr
from utils import *
from content import *
head_style = """
<style>
.main a {
color: blue;
text-decoration: underline;
}
@media (min-width: 1536px)
{
.gradio-container {
min-width: var(--size-full) !important;
}
}
</style>
"""
with gr.Blocks(title=f'{benchname} Leaderboard', head=head_style) as demo:
gr.Markdown(intro_md)
with gr.Tabs(elem_classes='tab-buttons') as tabs:
with gr.TabItem('🏅 Main Leaderboard', elem_id='main', id=0):
table, type_map = build_df()
headers = [coln for coln in table.columns if not coln.startswith('_')]
datatypes = [type_map[x] for x in headers]
colwidths = [80, 400, 120, 130] + [155 for _ in headers[4:]]
with gr.Row():
model_name = gr.Textbox(
value=search_default_val,
label='Model Name',
interactive=True,
visible=True,
)
model_size = gr.CheckboxGroup(
choices=MODEL_SIZE,
value=MODEL_SIZE,
label='Model Size',
interactive=True,
)
model_type = gr.CheckboxGroup(
choices=MODEL_TYPE,
value=MODEL_TYPE,
label='Model Type',
interactive=True,
)
data_component = gr.components.DataFrame(
value=table[headers],
type='pandas',
datatype=datatypes,
interactive=False,
wrap=True,
visible=True,
column_widths=colwidths,
)
def filter_df(model_name, model_size, model_type):
df = table.copy(deep=True)
df['_vis'] = [model_size_flag(x, model_size) for x in df['_parameters']]
df['_vis'] &= pd.Series([model_type_flag(df.iloc[i], model_type) for i in range(len(df))])
if model_name != search_default_val:
model_name_lower = model_name.lower()
df['_vis'] &= pd.Series([(model_name_lower in name.lower()) for name in df['_name'].tolist()])
df = df[df['_vis']]
df['Rank'] = list(range(1, len(df)+1))
ret = gr.components.DataFrame(
value=df[headers],
type='pandas',
datatype=datatypes,
interactive=False,
wrap=True,
visible=True,
column_widths=colwidths,
)
return ret
model_name.submit(filter_df, [model_name, model_size, model_type], data_component)
model_size.change(filter_df, [model_name, model_size, model_type], data_component)
model_type.change(filter_df, [model_name, model_size, model_type], data_component)
with gr.TabItem('📝 About', elem_id='about', id=1):
gr.Markdown(about_md)
with gr.TabItem('🚀 Submit your model', elem_id='submit', id=2):
gr.Markdown(submit_md)
# with gr.Row():
# with gr.Accordion('Citation', open=False):
# gr.Markdown(citation_md)
gr.Markdown(Bottom_logo)
if __name__=="__main__":
demo.launch()
|