Spaces:
Paused
Paused
Clémentine
commited on
Commit
•
3ae1b8c
1
Parent(s):
cd67f11
Now checkboxes for model filters selections
Browse files
app.py
CHANGED
@@ -231,9 +231,17 @@ def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
|
|
231 |
]
|
232 |
return filtered_df
|
233 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
234 |
|
235 |
def filter_models(
|
236 |
-
df: pd.DataFrame, current_columns_df: pd.DataFrame, type_query:
|
237 |
) -> pd.DataFrame:
|
238 |
current_columns = current_columns_df.columns
|
239 |
|
@@ -243,24 +251,12 @@ def filter_models(
|
|
243 |
else: # Show only still on the hub models
|
244 |
filtered_df = df[df[AutoEvalColumn.still_on_hub.name] == True][current_columns]
|
245 |
|
246 |
-
|
247 |
-
|
248 |
-
|
249 |
-
|
250 |
-
|
251 |
-
|
252 |
-
"all": (0, 10000),
|
253 |
-
"< 1B": (0, 1),
|
254 |
-
"~3B": (1, 5),
|
255 |
-
"~7B": (6, 11),
|
256 |
-
"~13B": (12, 15),
|
257 |
-
"~35B": (16, 55),
|
258 |
-
"60B+": (55, 10000),
|
259 |
-
}
|
260 |
-
numeric_interval = numeric_intervals[size_query]
|
261 |
-
params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
|
262 |
-
|
263 |
-
filtered_df = filtered_df[params_column.between(*numeric_interval)]
|
264 |
|
265 |
return filtered_df
|
266 |
|
@@ -313,31 +309,27 @@ with demo:
|
|
313 |
elem_id="search-bar",
|
314 |
)
|
315 |
with gr.Box(elem_id="box-filter"):
|
316 |
-
filter_columns_type = gr.
|
317 |
-
label="
|
318 |
choices=[
|
319 |
-
"all",
|
320 |
ModelType.PT.to_str(),
|
321 |
ModelType.FT.to_str(),
|
322 |
ModelType.IFT.to_str(),
|
323 |
ModelType.RL.to_str(),
|
324 |
],
|
325 |
-
value=
|
|
|
|
|
|
|
|
|
|
|
326 |
interactive=True,
|
327 |
elem_id="filter-columns-type",
|
328 |
)
|
329 |
-
filter_columns_size = gr.
|
330 |
-
label="
|
331 |
-
choices=
|
332 |
-
|
333 |
-
"< 1B",
|
334 |
-
"~3B",
|
335 |
-
"~7B",
|
336 |
-
"~13B",
|
337 |
-
"~35B",
|
338 |
-
"60B+",
|
339 |
-
],
|
340 |
-
value="all",
|
341 |
interactive=True,
|
342 |
elem_id="filter-columns-size",
|
343 |
)
|
|
|
231 |
]
|
232 |
return filtered_df
|
233 |
|
234 |
+
NUMERIC_INTERVALS = {
|
235 |
+
"< 1.5B": (0, 1.5),
|
236 |
+
"~3B": (1.5, 5),
|
237 |
+
"~7B": (6, 11),
|
238 |
+
"~13B": (12, 15),
|
239 |
+
"~35B": (16, 55),
|
240 |
+
"60B+": (55, 10000),
|
241 |
+
}
|
242 |
|
243 |
def filter_models(
|
244 |
+
df: pd.DataFrame, current_columns_df: pd.DataFrame, type_query: list, size_query: list, show_deleted: bool
|
245 |
) -> pd.DataFrame:
|
246 |
current_columns = current_columns_df.columns
|
247 |
|
|
|
251 |
else: # Show only still on the hub models
|
252 |
filtered_df = df[df[AutoEvalColumn.still_on_hub.name] == True][current_columns]
|
253 |
|
254 |
+
type_emoji = [t[0] for t in type_query]
|
255 |
+
filtered_df = filtered_df[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
|
256 |
+
|
257 |
+
numeric_interval = [NUMERIC_INTERVALS[s] for s in size_query]
|
258 |
+
params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
|
259 |
+
filtered_df = filtered_df[params_column.between(numeric_interval[0][0], numeric_interval[-1][-1])]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
260 |
|
261 |
return filtered_df
|
262 |
|
|
|
309 |
elem_id="search-bar",
|
310 |
)
|
311 |
with gr.Box(elem_id="box-filter"):
|
312 |
+
filter_columns_type = gr.CheckboxGroup(
|
313 |
+
label="Model types",
|
314 |
choices=[
|
|
|
315 |
ModelType.PT.to_str(),
|
316 |
ModelType.FT.to_str(),
|
317 |
ModelType.IFT.to_str(),
|
318 |
ModelType.RL.to_str(),
|
319 |
],
|
320 |
+
value=[
|
321 |
+
ModelType.PT.to_str(),
|
322 |
+
ModelType.FT.to_str(),
|
323 |
+
ModelType.IFT.to_str(),
|
324 |
+
ModelType.RL.to_str(),
|
325 |
+
],
|
326 |
interactive=True,
|
327 |
elem_id="filter-columns-type",
|
328 |
)
|
329 |
+
filter_columns_size = gr.CheckboxGroup(
|
330 |
+
label="Model sizes",
|
331 |
+
choices=list(NUMERIC_INTERVALS.keys()),
|
332 |
+
value=list(NUMERIC_INTERVALS.keys()),
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
333 |
interactive=True,
|
334 |
elem_id="filter-columns-size",
|
335 |
)
|