diff --git "a/data/output_plots.csv" "b/data/output_plots.csv" --- "a/data/output_plots.csv" +++ "b/data/output_plots.csv" @@ -2,120 +2,134 @@ plot_object,header,plot_json,df,arguments,description "Figure({ 'data': [{'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'legendgroup': 'Snorkel Mistral PairRM DPO (7B)', 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, - 'name': 'Mistral-7B-Instruct-v0.2', - 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'name': 'Snorkel Mistral PairRM DPO (7B)', + 'offsetgroup': 'Snorkel Mistral PairRM DPO (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([3.1836577]), + 'y': array([25.61907138]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'legendgroup': 'gpt-4', 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'name': 'gpt-4', + 'offsetgroup': 'gpt-4', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'x': array(['gpt-4'], dtype=object), 'xaxis': 'x', - 'y': array([6.88927143]), + 'y': array([17.68367981]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'legendgroup': 'gpt-4-turbo', 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'name': 'gpt-4-turbo', + 'offsetgroup': 'gpt-4-turbo', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'x': array(['gpt-4-turbo'], dtype=object), 'xaxis': 'x', - 'y': array([1.59549656]), + 'y': array([15.85205264]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'chat-bison', + 'legendgroup': '01-ai Yi Chat (34B)', 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'chat-bison', - 'offsetgroup': 'chat-bison', + 'name': '01-ai Yi Chat (34B)', + 'offsetgroup': '01-ai Yi Chat (34B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison'], dtype=object), + 'x': array(['01-ai Yi Chat (34B)'], dtype=object), 'xaxis': 'x', - 'y': array([3.89024363]), + 'y': array([10.45530375]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'chat-bison (PaLM 2)', + 'legendgroup': 'Chronos Hermes (13B)', 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'chat-bison (PaLM 2)', - 'offsetgroup': 'chat-bison (PaLM 2)', + 'name': 'Chronos Hermes (13B)', + 'offsetgroup': 'Chronos Hermes (13B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'x': array(['Chronos Hermes (13B)'], dtype=object), 'xaxis': 'x', - 'y': array([3.30885241]), + 'y': array([8.26602804]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'chat-bison-32k', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k', - 'offsetgroup': 'chat-bison-32k', + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison-32k'], dtype=object), + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), 'xaxis': 'x', - 'y': array([4.12817777]), + 'y': array([6.55972525]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', + 'legendgroup': 'llama-2-70b-chat', 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k (PaLM 2 32K)', - 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', + 'name': 'llama-2-70b-chat', + 'offsetgroup': 'llama-2-70b-chat', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), + 'x': array(['llama-2-70b-chat'], dtype=object), 'xaxis': 'x', - 'y': array([5.46443628]), + 'y': array([6.06536523]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gemini-pro', + 'legendgroup': 'WizardLM v1.2 (13B)', 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', + 'name': 'WizardLM v1.2 (13B)', + 'offsetgroup': 'WizardLM v1.2 (13B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), + 'x': array(['WizardLM v1.2 (13B)'], dtype=object), 'xaxis': 'x', - 'y': array([4.11187035]), + 'y': array([5.47183404]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gpt-3.5-turbo', + 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k (PaLM 2 32K)', + 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), + 'xaxis': 'x', + 'y': array([5.46443628]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-3.5-turbo', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, 'name': 'gpt-3.5-turbo', 'offsetgroup': 'gpt-3.5-turbo', 'orientation': 'v', @@ -128,50 +142,50 @@ plot_object,header,plot_json,df,arguments,description 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gpt-4', - 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, - 'name': 'gpt-4', - 'offsetgroup': 'gpt-4', + 'legendgroup': 'gemini-pro', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'gemini-pro', + 'offsetgroup': 'gemini-pro', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gpt-4'], dtype=object), + 'x': array(['gemini-pro'], dtype=object), 'xaxis': 'x', - 'y': array([17.68367981]), + 'y': array([4.11187035]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gpt-4-turbo', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, - 'name': 'gpt-4-turbo', - 'offsetgroup': 'gpt-4-turbo', + 'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gpt-4-turbo'], dtype=object), + 'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object), 'xaxis': 'x', - 'y': array([15.85205264]), + 'y': array([4.00486071]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'llama-2-70b-chat', - 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', + 'legendgroup': 'Vicuna v1.5 (7B)', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'Vicuna v1.5 (7B)', + 'offsetgroup': 'Vicuna v1.5 (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), + 'x': array(['Vicuna v1.5 (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([6.06536523]), + 'y': array([3.85941075]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', 'legendgroup': 'zephyr-7b-beta', - 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, 'name': 'zephyr-7b-beta', 'offsetgroup': 'zephyr-7b-beta', 'orientation': 'v', @@ -180,39 +194,167 @@ plot_object,header,plot_json,df,arguments,description 'type': 'bar', 'x': array(['zephyr-7b-beta'], dtype=object), 'xaxis': 'x', - 'y': array([3.38989453]), + 'y': array([3.57674572]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'LLaMA-2 Chat (7B)', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'LLaMA-2 Chat (7B)', + 'offsetgroup': 'LLaMA-2 Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['LLaMA-2 Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([3.44595034]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison (PaLM 2)', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'chat-bison (PaLM 2)', + 'offsetgroup': 'chat-bison (PaLM 2)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'xaxis': 'x', + 'y': array([3.30885241]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([3.1836577]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'OpenHermes-2.5-Mistral (7B)', + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'OpenHermes-2.5-Mistral (7B)', + 'offsetgroup': 'OpenHermes-2.5-Mistral (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.83201321]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Qwen 1.5 Chat (7B)', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': 'Qwen 1.5 Chat (7B)', + 'offsetgroup': 'Qwen 1.5 Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.22289769]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'RedPajama-INCITE Chat (7B)', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'name': 'RedPajama-INCITE Chat (7B)', + 'offsetgroup': 'RedPajama-INCITE Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([1.93642128]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.59549656]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Falcon Instruct (7B)', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Falcon Instruct (7B)', + 'offsetgroup': 'Falcon Instruct (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Falcon Instruct (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([1.35819112]), 'yaxis': 'y'}], 'layout': {'barmode': 'relative', 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, 'template': '...', 'title': {'text': 'Plot of execution time given the same input for summarization task'}, 'xaxis': {'anchor': 'y', - 'categoryarray': [Mistral-7B-Instruct-v0.2, + 'categoryarray': [Snorkel Mistral PairRM DPO (7B), gpt-4, + gpt-4-turbo, 01-ai Yi Chat (34B), + Chronos Hermes (13B), Mixtral-8x7B-Instruct-v0.1, + llama-2-70b-chat, WizardLM v1.2 (13B), + chat-bison-32k (PaLM 2 32K), + gpt-3.5-turbo, gemini-pro, Mistral (7B) + Instruct v0.2 (Together AI), Vicuna v1.5 + (7B), zephyr-7b-beta, LLaMA-2 Chat (7B), + chat-bison (PaLM 2), + Mistral-7B-Instruct-v0.2, + OpenHermes-2.5-Mistral (7B), Qwen 1.5 + Chat (7B), RedPajama-INCITE Chat (7B), TinyLlama/TinyLlama-1.1B-Chat-v1.0, - chat-bison, chat-bison (PaLM 2), chat- - bison-32k, chat-bison-32k (PaLM 2 32K), - gemini-pro, gpt-3.5-turbo, gpt-4, - gpt-4-turbo, llama-2-70b-chat, - zephyr-7b-beta], + Falcon Instruct (7B)], 'categoryorder': 'array', 'domain': [0.0, 1.0], 'title': {'text': 'Model'}}, 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution time (s)'}}} -})",Plot of execution time given the same input for summarization task,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time (s)=%{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"":[3.183657696204526],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time 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(s)=%{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"":[1.5954965559732053],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time (s)=%{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"":[3.890243631601334],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time (s)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""chat-bison (PaLM 2)"",""marker"":{""color"":""#FFA15A"",""pattern"":{""shape"":""""}},""name"":""chat-bison (PaLM 2)"",""offsetgroup"":""chat-bison (PaLM 2)"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""chat-bison (PaLM 2)""],""xaxis"":""x"",""y"":[3.3088524077087644],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time 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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. @@ -221,106 +363,120 @@ It is also important to note that we used litellm python library for all of the "Figure({ 'data': [{'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
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Output words count=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'legendgroup': 'llama-2-70b-chat', 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'name': 'llama-2-70b-chat', + 'offsetgroup': 'llama-2-70b-chat', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'x': array(['llama-2-70b-chat'], dtype=object), 'xaxis': 'x', - 'y': array([54.6203696]), + 'y': array([95.35066814]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'legendgroup': 'Chronos Hermes (13B)', 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'name': 'Chronos Hermes (13B)', + 'offsetgroup': 'Chronos Hermes (13B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'x': array(['Chronos Hermes (13B)'], dtype=object), 'xaxis': 'x', - 'y': array([32.55470546]), + 'y': array([72.67356172]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'chat-bison', + 'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'chat-bison', - 'offsetgroup': 'chat-bison', + 'name': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison'], dtype=object), + 'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object), 'xaxis': 'x', - 'y': array([49.]), + 'y': array([68.3833169]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'chat-bison (PaLM 2)', + 'legendgroup': 'LLaMA-2 Chat (7B)', 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'chat-bison (PaLM 2)', - 'offsetgroup': 'chat-bison (PaLM 2)', + 'name': 'LLaMA-2 Chat (7B)', + 'offsetgroup': 'LLaMA-2 Chat (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'x': array(['LLaMA-2 Chat (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([40.9371875]), + 'y': array([62.62490104]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'chat-bison-32k', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k', - 'offsetgroup': 'chat-bison-32k', + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison-32k'], dtype=object), + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), 'xaxis': 'x', - 'y': array([48.025]), + 'y': array([54.16817689]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', + 'legendgroup': '01-ai Yi Chat (34B)', 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k (PaLM 2 32K)', - 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', + 'name': '01-ai Yi Chat (34B)', + 'offsetgroup': '01-ai Yi Chat (34B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), + 'x': array(['01-ai Yi Chat (34B)'], dtype=object), 'xaxis': 'x', - 'y': array([38.72477679]), + 'y': array([44.55932188]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'gemini-pro', + 'legendgroup': 'chat-bison (PaLM 2)', 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'chat-bison (PaLM 2)', + 'offsetgroup': 'chat-bison (PaLM 2)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'xaxis': 'x', + 'y': array([40.9371875]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'gemini-pro', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, 'name': 'gemini-pro', 'offsetgroup': 'gemini-pro', 'orientation': 'v', @@ -334,7 +490,7 @@ It is also important to note that we used litellm python library for all of the {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', 'legendgroup': 'gpt-3.5-turbo', - 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, 'name': 'gpt-3.5-turbo', 'offsetgroup': 'gpt-3.5-turbo', 'orientation': 'v', @@ -347,22 +503,22 @@ It is also important to note that we used litellm python library for all of the 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'gpt-4', - 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, - 'name': 'gpt-4', - 'offsetgroup': 'gpt-4', + 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k (PaLM 2 32K)', + 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gpt-4'], dtype=object), + 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), 'xaxis': 'x', - 'y': array([32.90737496]), + 'y': array([38.72477679]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', 'legendgroup': 'gpt-4-turbo', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, 'name': 'gpt-4-turbo', 'offsetgroup': 'gpt-4-turbo', 'orientation': 'v', @@ -375,181 +531,295 @@ It is also important to note that we used litellm python library for all of the 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'llama-2-70b-chat', - 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', + 'legendgroup': 'Vicuna v1.5 (7B)', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'Vicuna v1.5 (7B)', + 'offsetgroup': 'Vicuna v1.5 (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), + 'x': array(['Vicuna v1.5 (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([95.35066814]), + 'y': array([37.18623469]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Output words count=%{y}', - 'legendgroup': 'zephyr-7b-beta', - 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'zephyr-7b-beta', - 'offsetgroup': 'zephyr-7b-beta', + 'legendgroup': 'OpenHermes-2.5-Mistral (7B)', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'OpenHermes-2.5-Mistral (7B)', + 'offsetgroup': 'OpenHermes-2.5-Mistral (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([32.90882368]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'gpt-4', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'gpt-4', + 'offsetgroup': 'gpt-4', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-4'], dtype=object), + 'xaxis': 'x', + 'y': array([32.90737496]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'Qwen 1.5 Chat (7B)', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'Qwen 1.5 Chat (7B)', + 'offsetgroup': 'Qwen 1.5 Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([32.61154087]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([32.55470546]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'zephyr-7b-beta', + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'zephyr-7b-beta', + 'offsetgroup': 'zephyr-7b-beta', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', 'x': array(['zephyr-7b-beta'], dtype=object), 'xaxis': 'x', - 'y': array([31.15925708]), + 'y': array([32.25400169]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'WizardLM v1.2 (13B)', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': 'WizardLM v1.2 (13B)', + 'offsetgroup': 'WizardLM v1.2 (13B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['WizardLM v1.2 (13B)'], dtype=object), + 'xaxis': 'x', + 'y': array([30.37805458]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([29.32127976]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'Falcon Instruct (7B)', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Falcon Instruct (7B)', + 'offsetgroup': 'Falcon Instruct (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Falcon Instruct (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([10.03811449]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Output words count=%{y}', + 'legendgroup': 'RedPajama-INCITE Chat (7B)', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'RedPajama-INCITE Chat (7B)', + 'offsetgroup': 'RedPajama-INCITE Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([5.25619503]), 'yaxis': 'y'}], 'layout': {'barmode': 'relative', 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, 'template': '...', 'title': {'text': 'Plot of output words count given the same input for summarization task'}, 'xaxis': {'anchor': 'y', - 'categoryarray': [Mistral-7B-Instruct-v0.2, - Mixtral-8x7B-Instruct-v0.1, + 'categoryarray': [Snorkel Mistral PairRM DPO (7B), + llama-2-70b-chat, Chronos Hermes (13B), + Mistral (7B) Instruct v0.2 (Together + AI), LLaMA-2 Chat (7B), + Mixtral-8x7B-Instruct-v0.1, 01-ai Yi + Chat (34B), chat-bison (PaLM 2), gemini- + pro, gpt-3.5-turbo, chat-bison-32k (PaLM + 2 32K), gpt-4-turbo, Vicuna v1.5 (7B), + OpenHermes-2.5-Mistral (7B), gpt-4, Qwen + 1.5 Chat (7B), TinyLlama/TinyLlama-1.1B-Chat-v1.0, - chat-bison, chat-bison (PaLM 2), chat- - bison-32k, chat-bison-32k (PaLM 2 32K), - gemini-pro, gpt-3.5-turbo, gpt-4, - gpt-4-turbo, llama-2-70b-chat, - zephyr-7b-beta], + zephyr-7b-beta, WizardLM v1.2 (13B), + Mistral-7B-Instruct-v0.2, Falcon + Instruct (7B), RedPajama-INCITE Chat + (7B)], 'categoryorder': 'array', 'domain': [0.0, 1.0], 'title': {'text': 'Model'}}, 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Output words count'}}} -})",Plot of output words count given the same input for summarization task,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eOutput words 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Chunks mean size (characters)=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'legendgroup': 'chat-bison (PaLM 2)', 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'name': 'chat-bison (PaLM 2)', + 'offsetgroup': 'chat-bison (PaLM 2)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'x': array(['chat-bison (PaLM 2)'], dtype=object), 'xaxis': 'x', - 'y': array([2.95690172]), + 'y': array([57.12081731]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'name': 'chat-bison-32k (PaLM 2 32K)', + 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), 'xaxis': 'x', - 'y': array([3.14663951]), + 'y': array([56.57639874]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'chat-bison', + 'legendgroup': 'Falcon Instruct (7B)', 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'chat-bison', - 'offsetgroup': 'chat-bison', + 'name': 'Falcon Instruct (7B)', + 'offsetgroup': 'Falcon Instruct (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison'], dtype=object), + 'x': array(['Falcon Instruct (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([61.46100879]), + 'y': array([3.98255342]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'chat-bison (PaLM 2)', + 'legendgroup': 'llama-2-70b-chat', 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'chat-bison (PaLM 2)', - 'offsetgroup': 'chat-bison (PaLM 2)', + 'name': 'llama-2-70b-chat', + 'offsetgroup': 'llama-2-70b-chat', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'x': array(['llama-2-70b-chat'], dtype=object), 'xaxis': 'x', - 'y': array([57.12081731]), + 'y': array([3.20032418]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'chat-bison-32k', + 'legendgroup': 'RedPajama-INCITE Chat (7B)', 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k', - 'offsetgroup': 'chat-bison-32k', + 'name': 'RedPajama-INCITE Chat (7B)', + 'offsetgroup': 'RedPajama-INCITE Chat (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['chat-bison-32k'], dtype=object), + 'x': array(['RedPajama-INCITE Chat (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([62.01633273]), + 'y': array([3.17457251]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'chat-bison-32k (PaLM 2 32K)', - 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), - 'xaxis': 'x', - 'y': array([56.57639874]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'gemini-pro', - 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), 'xaxis': 'x', - 'y': array([142.50301526]), + 'y': array([3.14663951]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', 'legendgroup': 'gpt-3.5-turbo', - 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, 'name': 'gpt-3.5-turbo', 'offsetgroup': 'gpt-3.5-turbo', 'orientation': 'v', @@ -563,7 +833,7 @@ It is also important to note that we used litellm python library for all of the {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', 'legendgroup': 'gpt-4', - 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, 'name': 'gpt-4', 'offsetgroup': 'gpt-4', 'orientation': 'v', @@ -577,7 +847,7 @@ It is also important to note that we used litellm python library for all of the {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', 'legendgroup': 'gpt-4-turbo', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, 'name': 'gpt-4-turbo', 'offsetgroup': 'gpt-4-turbo', 'orientation': 'v', @@ -590,22 +860,78 @@ It is also important to note that we used litellm python library for all of the 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'llama-2-70b-chat', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([2.95880337]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'LLaMA-2 Chat (7B)', 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', + 'name': 'LLaMA-2 Chat (7B)', + 'offsetgroup': 'LLaMA-2 Chat (7B)', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), + 'x': array(['LLaMA-2 Chat (7B)'], dtype=object), 'xaxis': 'x', - 'y': array([3.20032418]), + 'y': array([2.7744863]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', - 'legendgroup': 'zephyr-7b-beta', + 'legendgroup': 'Qwen 1.5 Chat (7B)', 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'Qwen 1.5 Chat (7B)', + 'offsetgroup': 'Qwen 1.5 Chat (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Qwen 1.5 Chat (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.76407305]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'Snorkel Mistral PairRM DPO (7B)', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'Snorkel Mistral PairRM DPO (7B)', + 'offsetgroup': 'Snorkel Mistral PairRM DPO (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.71983728]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'Chronos Hermes (13B)', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'Chronos Hermes (13B)', + 'offsetgroup': 'Chronos Hermes (13B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Chronos Hermes (13B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.71485241]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'zephyr-7b-beta', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, 'name': 'zephyr-7b-beta', 'offsetgroup': 'zephyr-7b-beta', 'orientation': 'v', @@ -614,37 +940,136 @@ It is also important to note that we used litellm python library for all of the 'type': 'bar', 'x': array(['zephyr-7b-beta'], dtype=object), 'xaxis': 'x', - 'y': array([2.71100327]), + 'y': array([2.70854999]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([2.69413923]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'offsetgroup': 'Mistral (7B) Instruct v0.2 (Together AI)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.63865224]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': '01-ai Yi Chat (34B)', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': '01-ai Yi Chat (34B)', + 'offsetgroup': '01-ai Yi Chat (34B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['01-ai Yi Chat (34B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.60737454]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'OpenHermes-2.5-Mistral (7B)', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'name': 'OpenHermes-2.5-Mistral (7B)', + 'offsetgroup': 'OpenHermes-2.5-Mistral (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.41139151]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'Vicuna v1.5 (7B)', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Vicuna v1.5 (7B)', + 'offsetgroup': 'Vicuna v1.5 (7B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Vicuna v1.5 (7B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.38783449]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Chunks mean size (characters)=%{y}', + 'legendgroup': 'WizardLM v1.2 (13B)', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'WizardLM v1.2 (13B)', + 'offsetgroup': 'WizardLM v1.2 (13B)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['WizardLM v1.2 (13B)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.29383365]), 'yaxis': 'y'}], 'layout': {'barmode': 'relative', 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, 'template': '...', 'title': {'text': 'Plot of chunks mean size given the same input for summarization task'}, 'xaxis': {'anchor': 'y', - 'categoryarray': [Mistral-7B-Instruct-v0.2, - Mixtral-8x7B-Instruct-v0.1, + 'categoryarray': [gemini-pro, chat-bison (PaLM 2), chat- + bison-32k (PaLM 2 32K), Falcon Instruct + (7B), llama-2-70b-chat, RedPajama-INCITE + Chat (7B), TinyLlama/TinyLlama-1.1B-Chat-v1.0, - chat-bison, chat-bison (PaLM 2), chat- - bison-32k, chat-bison-32k (PaLM 2 32K), - gemini-pro, gpt-3.5-turbo, gpt-4, - gpt-4-turbo, llama-2-70b-chat, - zephyr-7b-beta], + gpt-3.5-turbo, gpt-4, gpt-4-turbo, + Mixtral-8x7B-Instruct-v0.1, LLaMA-2 Chat + (7B), Qwen 1.5 Chat (7B), Snorkel + Mistral PairRM DPO (7B), Chronos Hermes + (13B), zephyr-7b-beta, + Mistral-7B-Instruct-v0.2, Mistral (7B) + Instruct v0.2 (Together AI), 01-ai Yi + Chat (34B), OpenHermes-2.5-Mistral (7B), + Vicuna v1.5 (7B), WizardLM v1.2 (13B)], 'categoryorder': 'array', 'domain': [0.0, 1.0], 'title': {'text': 'Model'}}, 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Chunks mean size (characters)'}}} -})",Plot of chunks mean size given the same input for summarization task,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eChunks mean size 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