2024-02-14 15:08:37 Publish script update

app.py

@@ -222,24 +222,6 @@ with gr.Blocks() as demo:
                 queries_config.base_query_template.replace("```", "'''"), output_types_df.to_markdown(index=False)
             )
         )
-    with gr.Tab("General plots"):
-        general_plots.apply(display_plot, axis=1)
-    with gr.Tab("Output characteristics"):
-        with gr.Row():
-            collapse_languages_button.render()
-            collapse_output_method_button.render()
-        summary_ui = gr.DataFrame(dataframe_style(summary_df), label="Output characteristics")
-        gr.Markdown(
-            """\
-This table compares output characteristics of different models which include execution time, output size and chunking of the output. Some providers and models don't support output chunking, in this case chunk related fields are left empty.
-
-Execution time refers to averaged time needed to execute one query.
-
-To count words we split the output string by whitespace `\w` regex character.
-
-Chunk sizes are measured in the characters count."""
-        )
-        output_plots.apply(display_plot, axis=1)
     with gr.Tab("Performance by time of the day"):
         # display only first plot for all models
         time_of_day_plots[0:1].apply(display_plot, axis=1)
@@ -256,11 +238,28 @@ Execution time refers to averaged time needed to execute one query.
 Hours and times of day in the table and in the plot are based on Central European Time.
                     
 Measurements were made during a normal work week.
+
+To compare providers we checked execution times for the same model `Mistral (7B) Instruct v0.2` on both Hugging Face and Together AI.
 """
         )
         # display rest of the plots
         time_of_day_plots[1:].apply(display_plot, axis=1)
+    with gr.Tab("Output characteristics"):
+        with gr.Row():
+            collapse_languages_button.render()
+            collapse_output_method_button.render()
+        summary_ui = gr.DataFrame(dataframe_style(summary_df), label="Output characteristics")
+        gr.Markdown(
+            """\
+This table compares output characteristics of different models which include execution time, output size and chunking of the output. Some providers and models don't support output chunking, in this case chunk related fields are left empty.
+
+Execution time refers to averaged time needed to execute one query.
+
+To count words we split the output string by whitespace `\w` regex character.
 
+Chunk sizes are measured in the characters count."""
+        )
+        output_plots.apply(display_plot, axis=1)
     with gr.Tab("Costs comparison"):
         models_costs_ui = gr.DataFrame(dataframe_style(model_costs_df), label="Costs comparison")
         gr.Markdown(
@@ -273,6 +272,14 @@ for models hosted this way we calculated "Cost Per Token" column using data coll
 Note that pause and resume time cost was not included in the "Cost Per Token" column calculation.
             """
         )
+        general_plots[general_plots.plot_name=="execution_costs"].apply(display_plot, axis=1)
+    with gr.Tab("Model dimensions"):
+        general_plots[general_plots.plot_name!="execution_costs"].apply(display_plot, axis=1)
+        gr.Markdown("""
+Model dimensions based on release blogs and documentation of their respective developers.
+
+Note that models, which dimensions were not disclosed publicly, were omitted from the plots.
+""")
     filter_button.click(
         fn=filter_dataframes,
         inputs=filter_textbox,

data/output_plots.csv

@@ -1,4 +1,4 @@
-plot_object,header,plot_json,df,arguments
+plot_object,header,plot_json,df,arguments,description
 "Figure({
     'data': [{'alignmentgroup': 'True',
               'hovertemplate': 'Model=%{x}<br>Execution time (s)=%{y}<extra></extra>',
@@ -213,10 +213,14 @@ plot_object,header,plot_json,df,arguments
 10,gpt-4-turbo,15.852052640759334
 11,llama-2-70b-chat,6.065365233652719
 12,zephyr-7b-beta,3.389894526934474
-","{""x"": ""model"", ""y"": ""execution_time"", ""color"": ""model"", ""labels"": {""model"": ""Model"", ""execution_time"": ""Execution time (s)""}, ""title"": ""Plot of execution time (s)""}"
+","{""x"": ""model"", ""y"": ""execution_time"", ""color"": ""model"", ""labels"": {""model"": ""Model"", ""execution_time"": ""Execution time (s)""}, ""title"": ""Plot of execution time (s)""}","This plot shows averaged response time for one query for each model.
+
+We used `time.time()` result saved to variable before making the call to API and compared it to `time.time()` result after receiving the results. 
+
+It is also important to note that we used litellm python library for all of the models which adds some overhead compared to pure curl calls."
 "Figure({
     'data': [{'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'Mistral-7B-Instruct-v0.2',
               'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
               'name': 'Mistral-7B-Instruct-v0.2',
@@ -230,7 +234,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([29.32127976]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'Mixtral-8x7B-Instruct-v0.1',
               'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
               'name': 'Mixtral-8x7B-Instruct-v0.1',
@@ -244,7 +248,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([54.6203696]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
               'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
               'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
@@ -258,7 +262,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([32.55470546]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'chat-bison',
               'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
               'name': 'chat-bison',
@@ -272,7 +276,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([49.]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'chat-bison (PaLM 2)',
               'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
               'name': 'chat-bison (PaLM 2)',
@@ -286,7 +290,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([40.9371875]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'chat-bison-32k',
               'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
               'name': 'chat-bison-32k',
@@ -300,7 +304,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([48.025]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'chat-bison-32k (PaLM 2 32K)',
               'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
               'name': 'chat-bison-32k (PaLM 2 32K)',
@@ -314,7 +318,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([38.72477679]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'gemini-pro',
               'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
               'name': 'gemini-pro',
@@ -328,7 +332,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([39.69346182]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'gpt-3.5-turbo',
               'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
               'name': 'gpt-3.5-turbo',
@@ -342,7 +346,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([39.25851284]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'gpt-4',
               'marker': {'color': '#FECB52', 'pattern': {'shape': ''}},
               'name': 'gpt-4',
@@ -356,7 +360,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([32.90737496]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'gpt-4-turbo',
               'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
               'name': 'gpt-4-turbo',
@@ -370,7 +374,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([38.36012473]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'llama-2-70b-chat',
               'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
               'name': 'llama-2-70b-chat',
@@ -384,7 +388,7 @@ plot_object,header,plot_json,df,arguments
               'y': array([95.35066814]),
               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Words count=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Output words count=%{y}<extra></extra>',
               'legendgroup': 'zephyr-7b-beta',
               'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
               'name': 'zephyr-7b-beta',
@@ -400,7 +404,7 @@ plot_object,header,plot_json,df,arguments
     'layout': {'barmode': 'relative',
                'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0},
                'template': '...',
-               'title': {'text': 'Plot of words count'},
+               'title': {'text': 'Plot of output words count'},
                'xaxis': {'anchor': 'y',
                          'categoryarray': [Mistral-7B-Instruct-v0.2,
                                            Mixtral-8x7B-Instruct-v0.1,
@@ -413,8 +417,8 @@ plot_object,header,plot_json,df,arguments
                          'categoryorder': 'array',
                          'domain': [0.0, 1.0],
                          'title': {'text': 'Model'}},
-               'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Words count'}}}
-})",Plot of words count,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eWords count=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Mistral-7B-Instruct-v0.2"",""marker"":{""color"":""#636efa"",""pattern"":{""shape"":""""}},""name"":""Mistral-7B-Instruct-v0.2"",""offsetgroup"":""Mistral-7B-Instruct-v0.2"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""Mistral-7B-Instruct-v0.2""],""xaxis"":""x"",""y"":[29.321279761904762],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eWords count=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Mixtral-8x7B-Instruct-v0.1"",""marker"":{""color"":""#EF553B"",""pattern"":{""shape"":""""}},""name"":""Mixtral-8x7B-Instruct-v0.1"",""offsetgroup"":""Mixtral-8x7B-Instruct-v0.1"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""Mixtral-8x7B-Instruct-v0.1""],""xaxis"":""x"",""y"":[54.620369597277694],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eWords count=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""TinyLlama\u002fTinyLlama-1.1B-Chat-v1.0"",""marker"":{""color"":""#00cc96"",""pattern"":{""shape"":""""}},""name"":""TinyLlama\u002fTinyLlama-1.1B-Chat-v1.0"",""offsetgroup"":""TinyLlama\u002fTinyLlama-1.1B-Chat-v1.0"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""TinyLlama\u002fTinyLlama-1.1B-Chat-v1.0""],""xaxis"":""x"",""y"":[32.55470545977011],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eWords count=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""chat-bison"",""marker"":{""color"":""#ab63fa"",""pattern"":{""shape"":""""}},""name"":""chat-bison"",""offsetgroup"":""chat-bison"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""chat-bison""],""xaxis"":""x"",""y"":[49.0],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eWords 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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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              {'alignmentgroup': 'True',
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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Chunks mean size (characters)=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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               'marker': {'color': '#FECB52', 'pattern': {'shape': ''}},
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               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Chunks mean size (characters)=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
               'legendgroup': 'gpt-4-turbo',
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               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Chunks mean size (characters)=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
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               'yaxis': 'y'},
              {'alignmentgroup': 'True',
-              'hovertemplate': 'Model=%{x}<br>Chunks mean size (characters)=%{y}<extra></extra>',
+              'hovertemplate': 'Model=%{x}<br>Chunks mean size (in characters)=%{y}<extra></extra>',
               'legendgroup': 'zephyr-7b-beta',
               'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
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                'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0},
                'template': '...',
-               'title': {'text': 'Plot of chunks mean size (characters)'},
+               'title': {'text': 'Plot of chunks mean size (in characters)'},
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                          'title': {'text': 'Model'}},
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 0,Mistral-7B-Instruct-v0.2,2.6941392346739055
 1,Mixtral-8x7B-Instruct-v0.1,2.9569017240855695
 2,TinyLlama/TinyLlama-1.1B-Chat-v1.0,3.146639511119026
@@ -643,4 +647,4 @@ plot_object,header,plot_json,df,arguments
 10,gpt-4-turbo,3.0126559039321035
 11,llama-2-70b-chat,3.2003241836714382
 12,zephyr-7b-beta,2.711003271075019
-","{""x"": ""model"", ""y"": ""chunk_sizes_mean"", ""color"": ""model"", ""labels"": {""model"": ""Model"", ""chunk_sizes_mean"": ""Chunks mean size (characters)""}, ""title"": ""Plot of chunks mean size (characters)""}"
+","{""x"": ""model"", ""y"": ""chunk_sizes_mean"", ""color"": ""model"", ""labels"": {""model"": ""Model"", ""chunk_sizes_mean"": ""Chunks mean size (in characters)""}, ""title"": ""Plot of chunks mean size (in characters)""}",

data/time_of_day_plots.csv

@@ -430,6 +430,45 @@ plot_object,header,plot_json,df,arguments
 184,zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667,Hugging Face Inference Endpoint
 185,zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667,Hugging Face Inference Endpoint
 ","{""x"": ""time_of_day"", ""y"": ""execution_time"", ""color"": ""model"", ""barmode"": ""group"", ""category_orders"": {""time_of_day"": [""early morning"", ""morning"", ""afternoon"", ""late afternoon"", ""evening"", ""late evening"", ""midnight"", ""night""]}, ""labels"": {""time_of_day"": ""Time of day"", ""execution_time"": ""Execution Time (s)"", ""model"": ""Model""}, ""title"": ""Execution time for different times of the day""}"
+"Figure({
+    'data': [{'hovertemplate': ('Provider=Hugging Face Inferenc' ... 'n Time (s)=%{y}<extra></extra>'),
+              'legendgroup': 'Hugging Face Inference Endpoint',
+              'line': {'color': '#636efa', 'dash': 'solid'},
+              'marker': {'symbol': 'circle'},
+              'mode': 'lines+markers',
+              'name': 'Hugging Face Inference Endpoint',
+              'orientation': 'v',
+              'showlegend': True,
+              'type': 'scatter',
+              'x': array(['morning', 'afternoon', 'late afternoon', 'evening'], dtype=object),
+              'xaxis': 'x',
+              'y': array([3.734026  , 3.22897372, 3.20486431, 3.39764007]),
+              'yaxis': 'y'},
+             {'hovertemplate': ('Provider=Together AI<br>Time o' ... 'n Time (s)=%{y}<extra></extra>'),
+              'legendgroup': 'Together AI',
+              'line': {'color': '#EF553B', 'dash': 'solid'},
+              'marker': {'symbol': 'circle'},
+              'mode': 'lines+markers',
+              'name': 'Together AI',
+              'orientation': 'v',
+              'showlegend': True,
+              'type': 'scatter',
+              'x': array(['morning', 'afternoon', 'late afternoon', 'evening'], dtype=object),
+              'xaxis': 'x',
+              'y': array([ 1.81441077,  3.43125006,  3.40168245, 11.98982314]),
+              'yaxis': 'y'}],
+    'layout': {'legend': {'title': {'text': 'Provider'}, 'tracegroupgap': 0},
+               'template': '...',
+               'title': {'text': 'Execution time for different times of the day for different providers'},
+               'xaxis': {'anchor': 'y',
+                         'categoryarray': [early morning, morning, afternoon, late
+                                           afternoon, evening, late evening,
+                                           midnight, night],
+                         'categoryorder': 'array',
+                         'domain': [0.0, 1.0],
+                         'title': {'text': 'Time of day'}},
+               'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution Time (s)'}}}
+})",Time of the day plot for different providers,"{""data"":[{""hovertemplate"":""Provider=Hugging Face Inference Endpoint\u003cbr\u003eTime of day=%{x}\u003cbr\u003eExecution Time (s)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Hugging Face Inference Endpoint"",""line"":{""color"":""#636efa"",""dash"":""solid""},""marker"":{""symbol"":""circle""},""mode"":""lines+markers"",""name"":""Hugging Face Inference Endpoint"",""orientation"":""v"",""showlegend"":true,""x"":[""morning"",""afternoon"",""late afternoon"",""evening""],""xaxis"":""x"",""y"":[3.734026002883911,3.228973722457886,3.2048643112182615,3.397640073299408],""yaxis"":""y"",""type"":""scatter""},{""hovertemplate"":""Provider=Together AI\u003cbr\u003eTime of day=%{x}\u003cbr\u003eExecution Time (s)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Together 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 "Figure({
     'data': [{'hovertemplate': 'Time of day=%{x}<br>Execution Time (s)=%{y}<extra></extra>',
               'legendgroup': '',

pipeline/models.py

@@ -190,7 +190,7 @@ MODELS = [
         "Together AI",
         input_size=4096,
     ),
-    Model("Vicuna v1.5 (7B)", "together_ai/lmsys/vicuna-7b-v1.5", None, "Together AI", input_size=4096, selected=True),
+    Model("Vicuna v1.5 (7B)", "together_ai/lmsys/vicuna-7b-v1.5", None, "Together AI", input_size=4096, size_billion_parameters=7, selected=True),
     Model(
         "Code Llama Instruct (13B)",
         "together_ai/codellama/CodeLlama-13b-Instruct-hf",
@@ -217,6 +217,7 @@ MODELS = [
         "together_ai/codellama/CodeLlama-7b-Instruct-hf",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=16384,
     ),
     Model(
@@ -224,6 +225,7 @@ MODELS = [
         "together_ai/togethercomputer/llama-2-13b-chat",
         None,
         "Together AI",
+        size_billion_parameters=13,
         input_size=4096,
     ),
     Model(
@@ -231,6 +233,7 @@ MODELS = [
         "together_ai/togethercomputer/llama-2-70b-chat",
         None,
         "Together AI",
+        size_billion_parameters=70,
         input_size=4096,
     ),
     Model(
@@ -238,6 +241,7 @@ MODELS = [
         "together_ai/togethercomputer/llama-2-7b-chat",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=4096,
         # selected=True,
     ),
@@ -246,6 +250,7 @@ MODELS = [
         "together_ai/mistralai/Mistral-7B-Instruct-v0.1",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=4096,
     ),
     Model(
@@ -253,6 +258,7 @@ MODELS = [
         "together_ai/mistralai/Mistral-7B-Instruct-v0.2",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=32768,
         selected=True,
     ),
@@ -261,6 +267,7 @@ MODELS = [
         "together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1",
         None,
         "Together AI",
+        size_billion_parameters=8*7,
         input_size=32768,
     ),
     Model(
@@ -268,6 +275,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Capybara-7B-V1p9",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=8192,
     ),
     Model(
@@ -275,6 +283,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
         None,
         "Together AI",
+        size_billion_parameters=8*7,
         input_size=32768,
     ),
     Model(
@@ -282,6 +291,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT",
         None,
         "Together AI",
+        size_billion_parameters=8*7,
         input_size=32768,
     ),
     Model(
@@ -289,6 +299,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Hermes-llama-2-7b",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=4096,
     ),
     Model(
@@ -296,6 +307,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Hermes-Llama2-13b",
         None,
         "Together AI",
+        size_billion_parameters=13,
         input_size=4096,
     ),
     Model(
@@ -303,6 +315,7 @@ MODELS = [
         "together_ai/NousResearch/Nous-Hermes-2-Yi-34B",
         None,
         "Together AI",
+        size_billion_parameters=34,
         input_size=4096,
     ),
     Model(
@@ -310,6 +323,7 @@ MODELS = [
         "together_ai/openchat/openchat-3.5-1210",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=8192,
     ),
     Model(
@@ -317,6 +331,7 @@ MODELS = [
         "together_ai/Open-Orca/Mistral-7B-OpenOrca",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=8192,
     ),
     Model(
@@ -324,6 +339,7 @@ MODELS = [
         "together_ai/togethercomputer/Qwen-7B-Chat",
         None,
         "Together AI",
+        size_billion_parameters=7,
         input_size=8192,
     ),
     Model(
@@ -331,6 +347,7 @@ MODELS = [
         "together_ai/Qwen/Qwen1.5-0.5B-Chat",
         None,
         "Together AI",
+        size_billion_parameters=0.5,
         input_size=32768,
     ),
     Model(
@@ -339,16 +356,18 @@ MODELS = [
         None,
         "Together AI",
         input_size=32768,
+        size_billion_parameters=1.8,
     ),
     Model(
         "Qwen 1.5 Chat (4B)",
         "together_ai/Qwen/Qwen1.5-4B-Chat",
         None,
         "Together AI",
+        size_billion_parameters=4,
         input_size=32768,
     ),
     Model(
-        "Qwen 1.5 Chat (7B)", "together_ai/Qwen/Qwen1.5-7B-Chat", None, "Together AI", input_size=32768, 
+        "Qwen 1.5 Chat (7B)", "together_ai/Qwen/Qwen1.5-7B-Chat", None, "Together AI", input_size=32768, size_billion_parameters=7
         # selected=True
     ),
     Model(
@@ -356,6 +375,7 @@ MODELS = [
         "together_ai/Qwen/Qwen1.5-14B-Chat",
         None,
         "Together AI",
+        size_billion_parameters=14,
         input_size=32768,
     ),
     Model(
@@ -422,6 +442,7 @@ MODELS = [
         "together_ai/togethercomputer/RedPajama-INCITE-Chat-3B-v1",
         None,
         "Together AI",
+        size_billion_parameters=3,
         input_size=2048,
     ),
     Model(
@@ -430,6 +451,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=2048,
+        size_billion_parameters=7,
         # selected=True,
     ),
     Model(
@@ -438,6 +460,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=32768,
+        size_billion_parameters=7,
     ),
     Model(
         "ReMM SLERP L2 (13B)",
@@ -445,6 +468,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=4096,
+        size_billion_parameters=13,
     ),
     Model(
         "Toppy M (7B)",
@@ -452,6 +476,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=4096,
+        size_billion_parameters=7
     ),
     Model(
         "WizardLM v1.2 (13B)",
@@ -459,6 +484,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=4096,
+        size_billion_parameters=13,
         # selected=True,
     ),
     Model(
@@ -467,6 +493,7 @@ MODELS = [
         None,
         "Together AI",
         input_size=4096,
+        size_billion_parameters=11,
         # selected=True,
     ),
 ]