eduardo-alvarez
commited on
Commit
•
47f3547
1
Parent(s):
6d60fea
adding hyperlinks to models
Browse files
app.py
CHANGED
@@ -166,9 +166,15 @@ with demo:
|
|
166 |
label="Model Types",
|
167 |
elem_id="model_types",
|
168 |
value=["pretrained","fine-tuned","chat-models","merges/moerges"])
|
169 |
-
|
|
|
|
|
|
|
|
|
|
|
170 |
initial_df = pd.read_csv("./status/leaderboard_status_041624.csv")
|
171 |
-
initial_df["Model"] =
|
|
|
172 |
|
173 |
def update_df(hw_selected, platform_selected, affiliation_selected, size_selected, precision_selected, type_selected):
|
174 |
filtered_df = filter_benchmarks_table(df=initial_df, hw_selected=hw_selected, platform_selected=platform_selected,
|
@@ -176,6 +182,7 @@ with demo:
|
|
176 |
precision_selected=precision_selected, type_selected=type_selected)
|
177 |
return filtered_df
|
178 |
|
|
|
179 |
initial_filtered_df = update_df(["Gaudi","Xeon","GPU Max","Arc GPU","Core Ultra"],
|
180 |
["Intel Developer Cloud","AWS","Azure","Google Cloud Platform","Local"],
|
181 |
["No Affiliation","Intel Innovator","Student Ambassador","Intel Liftoff", "Intel Engineering", "Other"],
|
@@ -183,10 +190,12 @@ with demo:
|
|
183 |
["fp32","fp16","bf16","int8","fp8", "int4"],
|
184 |
["pretrained","fine-tuned","chat-models","merges/moerges"])
|
185 |
|
|
|
186 |
gradio_df_display = gr.Dataframe(value=initial_filtered_df, headers=["Model","Average","Hardware","Model Type","Precision",
|
187 |
"Size","Infrastructure","ARC","HellaSwag","MMLU",
|
188 |
"TruthfulQA","Winogrande","Affiliation"],
|
189 |
-
datatype=["
|
|
|
190 |
|
191 |
filter_hw.change(fn=update_df,
|
192 |
inputs=[filter_hw, filter_platform, filter_affiliation, filter_size, filter_precision, filter_type],
|
|
|
166 |
label="Model Types",
|
167 |
elem_id="model_types",
|
168 |
value=["pretrained","fine-tuned","chat-models","merges/moerges"])
|
169 |
+
|
170 |
+
color = '#5750DC'
|
171 |
+
def make_clickable(row):
|
172 |
+
return f'<a href="https://huggingface.co/{row["Model"]}" target="_blank" style="color: {color}; text-decoration: underline;">{row["Model"]}</a>'
|
173 |
+
|
174 |
+
|
175 |
initial_df = pd.read_csv("./status/leaderboard_status_041624.csv")
|
176 |
+
initial_df["Model"] = initial_df.apply(make_clickable, axis=1)
|
177 |
+
|
178 |
|
179 |
def update_df(hw_selected, platform_selected, affiliation_selected, size_selected, precision_selected, type_selected):
|
180 |
filtered_df = filter_benchmarks_table(df=initial_df, hw_selected=hw_selected, platform_selected=platform_selected,
|
|
|
182 |
precision_selected=precision_selected, type_selected=type_selected)
|
183 |
return filtered_df
|
184 |
|
185 |
+
|
186 |
initial_filtered_df = update_df(["Gaudi","Xeon","GPU Max","Arc GPU","Core Ultra"],
|
187 |
["Intel Developer Cloud","AWS","Azure","Google Cloud Platform","Local"],
|
188 |
["No Affiliation","Intel Innovator","Student Ambassador","Intel Liftoff", "Intel Engineering", "Other"],
|
|
|
190 |
["fp32","fp16","bf16","int8","fp8", "int4"],
|
191 |
["pretrained","fine-tuned","chat-models","merges/moerges"])
|
192 |
|
193 |
+
|
194 |
gradio_df_display = gr.Dataframe(value=initial_filtered_df, headers=["Model","Average","Hardware","Model Type","Precision",
|
195 |
"Size","Infrastructure","ARC","HellaSwag","MMLU",
|
196 |
"TruthfulQA","Winogrande","Affiliation"],
|
197 |
+
datatype=["html","str","str","str","str","str","str","str","str","str","str","str","str"],
|
198 |
+
interactive=False)
|
199 |
|
200 |
filter_hw.change(fn=update_df,
|
201 |
inputs=[filter_hw, filter_platform, filter_affiliation, filter_size, filter_precision, filter_type],
|