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piotr-szleg-bards-ai
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·
95117cd
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Parent(s):
74c94d1
2024-02-15 13:26:46 Publish script update
Browse files- app.py +26 -34
- data/general_plots.csv +55 -39
- data/time_of_day_plots.csv +0 -0
- pipeline/models.py +70 -56
app.py
CHANGED
@@ -1,12 +1,11 @@
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import re
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import gradio as gr
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import pandas as pd
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import plotly
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import io
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import plotly.express as px
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import json
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from pandas.api.types import is_numeric_dtype
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from pipeline.config import LLMBoardConfig, QueriesConfig
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@@ -120,15 +119,12 @@ def dataframes():
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def for_dataframe(df):
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if not searched_model_names:
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return df
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return dataframe_style(pd.concat(
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df[df.model.str.lower().str.contains(n)]
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for n in searched_model_names
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))
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return (
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for_dataframe(summary_df_processed),
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for_dataframe(time_of_day_comparison_df),
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for_dataframe(model_costs_df)
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)
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@@ -161,7 +157,8 @@ last_textbox = 0
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plots = []
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single_model_plots = []
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-
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searched_model_names = searched_query.split("|")
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searched_model_names = [n.lower().strip() for n in searched_model_names]
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searched_model_names = [n for n in searched_model_names if n]
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@@ -169,11 +166,8 @@ def filter_plots(searched_query:str):
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def filter_dataframe(df):
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if not searched_model_names:
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return df
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return pd.concat(
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for n in searched_model_names
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)
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results = []
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for plot_display, plot, row in plots:
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visible = True
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@@ -181,31 +175,27 @@ def filter_plots(searched_query:str):
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buffer = io.StringIO(row["df"])
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df = pd.read_csv(buffer)
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df = filter_dataframe(df)
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plot = px.bar(
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df,
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**json.loads(row["arguments"])
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)
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plot.update_layout(autosize=True)
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elif "for model" in row["header"] and searched_model_names:
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plot_model = row["header"].split("for model")[1].lower()
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if not any(n in plot_model for n in searched_model_names):
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visible = False
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results.append(gr.Plot(plot, visible=visible))
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return results
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def display_plot(plot_df_row):
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row = dict(plot_df_row)
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plot = plotly.io.from_json(row["plot_json"])
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plot.update_layout(autosize=True)
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plots.append((
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gr.Plot(plot, label=row["header"], scale=1),
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plot,
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row))
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if "description" in row and pd.notna(row["description"]):
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gr.Markdown(str(row["description"]))
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with gr.Blocks() as demo:
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gr.HTML("<h1>Performance LLM Board</h1>")
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@@ -213,7 +203,7 @@ with gr.Blocks() as demo:
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filter_textbox.render()
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filter_button.render()
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gr.Markdown(
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)
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with gr.Tab("About this project"):
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@@ -238,8 +228,6 @@ Execution time refers to averaged time needed to execute one query.
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Hours and times of day in the table and in the plot are based on Central European Time.
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Measurements were made during a normal work week.
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To compare providers we checked execution times for the same model `Mistral (7B) Instruct v0.2` on both Hugging Face and Together AI.
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"""
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)
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# display rest of the plots
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@@ -272,14 +260,18 @@ for models hosted this way we calculated "Cost Per Token" column using data coll
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Note that pause and resume time cost was not included in the "Cost Per Token" column calculation.
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"""
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)
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general_plots[general_plots.plot_name=="execution_costs"].apply(display_plot, axis=1)
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with gr.Tab("
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general_plots[general_plots.plot_name!="execution_costs"].apply(display_plot, axis=1)
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gr.Markdown(
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filter_button.click(
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fn=filter_dataframes,
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inputs=filter_textbox,
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import io
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import json
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import re
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import gradio as gr
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import pandas as pd
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import plotly
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import plotly.express as px
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from pandas.api.types import is_numeric_dtype
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from pipeline.config import LLMBoardConfig, QueriesConfig
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def for_dataframe(df):
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if not searched_model_names:
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return df
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return dataframe_style(pd.concat(df[df.model.str.lower().str.contains(n)] for n in searched_model_names))
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return (
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for_dataframe(summary_df_processed),
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for_dataframe(time_of_day_comparison_df),
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for_dataframe(model_costs_df),
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)
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plots = []
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single_model_plots = []
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def filter_plots(searched_query: str):
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searched_model_names = searched_query.split("|")
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searched_model_names = [n.lower().strip() for n in searched_model_names]
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searched_model_names = [n for n in searched_model_names if n]
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def filter_dataframe(df):
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if not searched_model_names:
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return df
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return pd.concat(df[df.model.str.lower().str.contains(n)] for n in searched_model_names)
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results = []
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for plot_display, plot, row in plots:
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visible = True
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buffer = io.StringIO(row["df"])
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df = pd.read_csv(buffer)
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df = filter_dataframe(df)
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plot = px.bar(df, **json.loads(row["arguments"]))
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plot.update_layout(autosize=True)
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elif "for model" in row["header"] and searched_model_names:
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plot_model = row["header"].split("for model")[1].lower()
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if not any(n in plot_model for n in searched_model_names):
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visible = False
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results.append(gr.Plot(plot, visible=visible))
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return results
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def display_plot(plot_df_row):
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row = dict(plot_df_row)
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plot = plotly.io.from_json(row["plot_json"])
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plot.update_layout(autosize=True)
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plots.append((gr.Plot(plot, label=row["header"], scale=1), plot, row))
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if "description" in row and pd.notna(row["description"]):
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gr.Markdown(str(row["description"]))
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with gr.Blocks() as demo:
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gr.HTML("<h1>Performance LLM Board</h1>")
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filter_textbox.render()
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filter_button.render()
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gr.Markdown(
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' \* You can use `|` operator to display multiple models at once, for example "gpt|mistral|zephyr"'
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)
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with gr.Tab("About this project"):
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Hours and times of day in the table and in the plot are based on Central European Time.
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Measurements were made during a normal work week.
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"""
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)
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# display rest of the plots
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Note that pause and resume time cost was not included in the "Cost Per Token" column calculation.
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"""
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)
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general_plots[general_plots.plot_name == "execution_costs"].apply(display_plot, axis=1)
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with gr.Tab("Context length and parameters count"):
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general_plots[general_plots.plot_name != "execution_costs"].apply(display_plot, axis=1)
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gr.Markdown(
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"""
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LLM models context length and parameters count are based on release blogs and documentation of their respective developers.
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A lot of models had to be omitted due to their developers not disclosing their parameters count.
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Mainly OpenAI's GPT models and Google's Palm 2.
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"""
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)
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filter_button.click(
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fn=filter_dataframes,
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inputs=filter_textbox,
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data/general_plots.csv
CHANGED
@@ -10,7 +10,7 @@ execution_costs,./html/plots/execution_costs.html,"Figure({
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['gpt-4'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['gpt-4-turbo'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['gpt-3.5-turbo'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['llama-2-70b-chat'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['gemini-pro'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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'x': array([0.
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'xaxis': 'x',
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'y': array(['chat-bison (PaLM 2)'], dtype=object),
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'yaxis': 'y'},
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'showlegend': True,
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'textposition': 'auto',
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'type': 'bar',
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-
'x': array([0.
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'xaxis': 'x',
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'y': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object),
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'yaxis': 'y'}],
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'layout': {'barmode': 'relative',
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'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0},
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'title': {'text': 'Costs of execution of 20 test queries per model'},
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'xaxis': {'anchor': 'y', 'domain': [0.0, 1.0], 'title': {'text': 'Execution cost ($)'}},
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'yaxis': {'anchor': 'x',
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'categoryarray': [
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(PaLM 2), gemini-pro,
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Mixtral-8x7B-Instruct-v0.1,
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llama-2-70b-chat, gpt-3.5-turbo,
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'categoryorder': 'array',
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'domain': [0.0, 1.0],
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'title': {'text': 'Model'}}}
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-
})",Costs of execution of 20 test queries per model,,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost ($)=%{x}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""gpt-4"",""marker"":{""color"":""#636efa"",""pattern"":{""shape"":""""}},""name"":""gpt-4"",""offsetgroup"":""gpt-4"",""orientation"":""h"",""showlegend"":true,""textposition"":""auto"",""x"":[0.0249],""xaxis"":""x"",""y"":[""gpt-4""],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost ($)=%{x}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""gpt-4-turbo"",""marker"":{""color"":""#EF553B"",""pattern"":{""shape"":""""}},""name"":""gpt-4-turbo"",""offsetgroup"":""gpt-4-turbo"",""orientation"":""h"",""showlegend"":true,""textposition"":""auto"",""x"":[0.0229],""xaxis"":""x"",""y"":[""gpt-4-turbo""],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost ($)=%{x}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""gpt-3.5-turbo"",""marker"":{""color"":""#00cc96"",""pattern"":{""shape"":""""}},""name"":""gpt-3.5-turbo"",""offsetgroup"":""gpt-3.5-turbo"",""orientation"":""h"",""showlegend"":true,""textposition"":""auto"",""x"":[0.00083],""xaxis"":""x"",""y"":[""gpt-3.5-turbo""],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost ($)=%{x}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""llama-2-70b-chat"",""marker"":{""color"":""#ab63fa"",""pattern"":{""shape"":""""}},""name"":""llama-2-70b-chat"",""offsetgroup"":""llama-2-70b-chat"",""orientation"":""h"",""showlegend"":true,""textposition"":""auto"",""x"":[0.000711],""xaxis"":""x"",""y"":[""llama-2-70b-chat""],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost ($)=%{x}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Mixtral-8x7B-Instruct-v0.1"",""marker"":{""color"":""#FFA15A"",""pattern"":{""shape"":""""}},""name"":""Mixtral-8x7B-Instruct-v0.1"",""offsetgroup"":""Mixtral-8x7B-Instruct-v0.1"",""orientation"":""h"",""showlegend"":true,""textposition"":""auto"",""x"":[0.000711],""xaxis"":""x"",""y"":[""Mixtral-8x7B-Instruct-v0.1""],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{y}\u003cbr\u003eExecution cost 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2,0.
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1,0.
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0,0.
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3,0.
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4,0.
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8,0.
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9,0.
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10,0.
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"
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model_sizes,./html/plots/model_sizes.html,"Figure({
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'data': [{'alignmentgroup': 'True',
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@@ -337,9 +353,9 @@ model_sizes,./html/plots/model_sizes.html,"Figure({
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|
337 |
9,7.0,RedPajama-INCITE Chat (7B)
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338 |
4,1.1,TinyLlama/TinyLlama-1.1B-Chat-v1.0
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"
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340 |
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'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
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'name': 'gpt-4-turbo',
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@@ -353,7 +369,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['gpt-4-turbo'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
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'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
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'name': 'Mistral (7B) Instruct v0.2 (Together AI)',
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@@ -367,7 +383,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['Mistral (7B) Instruct v0.2 (Together AI)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Snorkel Mistral PairRM DPO (7B)',
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'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
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'name': 'Snorkel Mistral PairRM DPO (7B)',
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@@ -381,7 +397,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['Snorkel Mistral PairRM DPO (7B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Qwen 1.5 Chat (7B)',
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'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
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'name': 'Qwen 1.5 Chat (7B)',
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@@ -395,7 +411,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['Qwen 1.5 Chat (7B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'legendgroup': 'gpt-4',
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'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
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'name': 'gpt-4',
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@@ -409,7 +425,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['gpt-4'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'chat-bison (PaLM 2)',
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'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
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'name': 'chat-bison (PaLM 2)',
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@@ -423,7 +439,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['chat-bison (PaLM 2)'], dtype=object),
|
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'yaxis': 'y'},
|
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{'alignmentgroup': 'True',
|
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'hovertemplate': 'Model=%{y}<br>Model
|
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'legendgroup': 'OpenHermes-2.5-Mistral (7B)',
|
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'marker': {'color': '#FF6692', 'pattern': {'shape': ''}},
|
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'name': 'OpenHermes-2.5-Mistral (7B)',
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@@ -437,7 +453,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
|
|
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'y': array(['OpenHermes-2.5-Mistral (7B)'], dtype=object),
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'yaxis': 'y'},
|
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{'alignmentgroup': 'True',
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|
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'legendgroup': 'gpt-3.5-turbo',
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'marker': {'color': '#B6E880', 'pattern': {'shape': ''}},
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'name': 'gpt-3.5-turbo',
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@@ -451,7 +467,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['gpt-3.5-turbo'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'legendgroup': 'WizardLM v1.2 (13B)',
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'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}},
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'name': 'WizardLM v1.2 (13B)',
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@@ -465,7 +481,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['WizardLM v1.2 (13B)'], dtype=object),
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'yaxis': 'y'},
|
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
|
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'legendgroup': 'LLaMA-2 Chat (7B)',
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'marker': {'color': '#FECB52', 'pattern': {'shape': ''}},
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'name': 'LLaMA-2 Chat (7B)',
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@@ -479,7 +495,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['LLaMA-2 Chat (7B)'], dtype=object),
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'yaxis': 'y'},
|
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
|
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'legendgroup': 'Vicuna v1.5 (7B)',
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'marker': {'color': '#636efa', 'pattern': {'shape': ''}},
|
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'name': 'Vicuna v1.5 (7B)',
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@@ -493,7 +509,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['Vicuna v1.5 (7B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': '01-ai Yi Chat (34B)',
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'marker': {'color': '#EF553B', 'pattern': {'shape': ''}},
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'name': '01-ai Yi Chat (34B)',
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@@ -507,7 +523,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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|
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'y': array(['01-ai Yi Chat (34B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Upstage SOLAR Instruct v1 (11B)',
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'marker': {'color': '#00cc96', 'pattern': {'shape': ''}},
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'name': 'Upstage SOLAR Instruct v1 (11B)',
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@@ -521,7 +537,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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|
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'y': array(['Upstage SOLAR Instruct v1 (11B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Chronos Hermes (13B)',
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'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}},
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'name': 'Chronos Hermes (13B)',
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@@ -535,7 +551,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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|
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'y': array(['Chronos Hermes (13B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'Falcon Instruct (7B)',
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'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}},
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'name': 'Falcon Instruct (7B)',
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@@ -549,7 +565,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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|
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'y': array(['Falcon Instruct (7B)'], dtype=object),
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'yaxis': 'y'},
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{'alignmentgroup': 'True',
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'hovertemplate': 'Model=%{y}<br>Model
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'legendgroup': 'RedPajama-INCITE Chat (7B)',
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'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}},
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'name': 'RedPajama-INCITE Chat (7B)',
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@@ -563,7 +579,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'y': array(['RedPajama-INCITE Chat (7B)'], dtype=object),
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'yaxis': 'y'},
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'legendgroup': 'llama-2-70b-chat',
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@@ -579,8 +595,8 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'layout': {'barmode': 'relative',
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(7B), Falcon Instruct (7B), Chronos
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@@ -596,7 +612,7 @@ model_input_sizes,./html/plots/model_input_sizes.html,"Figure({
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'categoryorder': 'array',
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2,0.1446,gpt-4
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1,0.056,gpt-4-turbo
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0,0.00442,gpt-3.5-turbo
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3,0.002808,llama-2-70b-chat
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4,0.0020700000000000002,Mixtral-8x7B-Instruct-v0.1
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7,0.0006276866594950359,TinyLlama/TinyLlama-1.1B-Chat-v1.0
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9,7.0,RedPajama-INCITE Chat (7B)
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4,1.1,TinyLlama/TinyLlama-1.1B-Chat-v1.0
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'legendgroup': 'Mistral (7B) Instruct v0.2 (Together AI)',
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'legendgroup': 'Chronos Hermes (13B)',
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'legendgroup': 'Falcon Instruct (7B)',
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{'alignmentgroup': 'True',
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context length (tokens)""}},""yaxis"":{""anchor"":""x"",""domain"":[0.0,1.0],""title"":{""text"":""Model""},""categoryorder"":""array"",""categoryarray"":[""llama-2-70b-chat"",""RedPajama-INCITE Chat (7B)"",""Falcon Instruct (7B)"",""Chronos Hermes (13B)"",""Upstage SOLAR Instruct v1 (11B)"",""01-ai Yi Chat (34B)"",""Vicuna v1.5 (7B)"",""LLaMA-2 Chat (7B)"",""WizardLM v1.2 (13B)"",""gpt-3.5-turbo"",""OpenHermes-2.5-Mistral (7B)"",""chat-bison (PaLM 2)"",""gpt-4"",""Qwen 1.5 Chat (7B)"",""Snorkel Mistral PairRM DPO (7B)"",""Mistral (7B) Instruct v0.2 (Together AI)"",""gpt-4-turbo""]},""legend"":{""title"":{""text"":""Model""},""tracegroupgap"":0},""title"":{""text"":""Model context lengths in tokens""},""barmode"":""relative""}}","{""x"": ""model_context_lengths"", ""y"": ""model"", ""color"": ""model"", ""orientation"": ""h"", ""title"": ""Model context lengths in tokens"", ""labels"": {""model"": ""Model"", ""model_context_lengths"": ""Model context length (tokens)""}}",",model_context_lengths,model
|
616 |
1,128000,gpt-4-turbo
|
617 |
9,32768,Mistral (7B) Instruct v0.2 (Together AI)
|
618 |
11,32768,Snorkel Mistral PairRM DPO (7B)
|
data/time_of_day_plots.csv
CHANGED
The diff for this file is too large to render.
See raw diff
|
|
pipeline/models.py
CHANGED
@@ -15,7 +15,7 @@ class Model(object):
|
|
15 |
cost_per_million_tokens: int = None
|
16 |
cost_per_million_input_tokens: int = None
|
17 |
cost_per_million_output_tokens: int = None
|
18 |
-
|
19 |
selected: bool = False
|
20 |
|
21 |
def __post_init__(self):
|
@@ -48,7 +48,7 @@ MODELS = [
|
|
48 |
cost_per_million_input_tokens=1,
|
49 |
cost_per_million_output_tokens=2,
|
50 |
# https://learn.microsoft.com/en-us/answers/questions/1356487/what-is-the-exact-maximum-input-tokens-of-azure-gp
|
51 |
-
|
52 |
),
|
53 |
Model(
|
54 |
"gpt-4-turbo",
|
@@ -59,7 +59,7 @@ MODELS = [
|
|
59 |
cost_per_million_input_tokens=10,
|
60 |
cost_per_million_output_tokens=30,
|
61 |
# https://writesonic.com/blog/gpt-4-turbo-vs-gpt-4
|
62 |
-
|
63 |
),
|
64 |
Model(
|
65 |
"gpt-4",
|
@@ -69,7 +69,7 @@ MODELS = [
|
|
69 |
supports_functions=True,
|
70 |
cost_per_million_input_tokens=30,
|
71 |
cost_per_million_output_tokens=60,
|
72 |
-
|
73 |
),
|
74 |
# source: https://www.together.ai/pricing
|
75 |
Model(
|
@@ -80,7 +80,7 @@ MODELS = [
|
|
80 |
cost_per_million_tokens=0.9,
|
81 |
size_billion_parameters=70,
|
82 |
# https://github.com/facebookresearch/llama/issues/148
|
83 |
-
|
84 |
),
|
85 |
Model(
|
86 |
"Mixtral-8x7B-Instruct-v0.1",
|
@@ -106,6 +106,7 @@ MODELS = [
|
|
106 |
"Hugging Face Inference Endpoint",
|
107 |
hourly_cost=1.30,
|
108 |
size_billion_parameters=7,
|
|
|
109 |
),
|
110 |
Model(
|
111 |
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
|
@@ -134,7 +135,7 @@ MODELS = [
|
|
134 |
cost_per_million_input_tokens=0.25,
|
135 |
cost_per_million_output_tokens=0.5,
|
136 |
# https://ai.google.dev/models/palm
|
137 |
-
|
138 |
),
|
139 |
Model(
|
140 |
"chat-bison-32k (PaLM 2 32K)",
|
@@ -151,7 +152,7 @@ MODELS = [
|
|
151 |
"together_ai/zero-one-ai/Yi-34B-Chat",
|
152 |
None,
|
153 |
"Together AI",
|
154 |
-
|
155 |
# selected=True,
|
156 |
),
|
157 |
Model(
|
@@ -159,7 +160,7 @@ MODELS = [
|
|
159 |
"together_ai/Austism/chronos-hermes-13b",
|
160 |
None,
|
161 |
"Together AI",
|
162 |
-
|
163 |
# selected=True,
|
164 |
),
|
165 |
Model(
|
@@ -167,50 +168,58 @@ MODELS = [
|
|
167 |
"together_ai/deepseek-ai/deepseek-coder-33b-instruct",
|
168 |
None,
|
169 |
"Together AI",
|
170 |
-
|
171 |
),
|
172 |
Model(
|
173 |
"Platypus2 Instruct (70B)",
|
174 |
"together_ai/garage-bAInd/Platypus2-70B-instruct",
|
175 |
None,
|
176 |
"Together AI",
|
177 |
-
|
178 |
),
|
179 |
Model(
|
180 |
"MythoMax-L2 (13B)",
|
181 |
"together_ai/Gryphe/MythoMax-L2-13b",
|
182 |
None,
|
183 |
"Together AI",
|
184 |
-
|
185 |
),
|
186 |
Model(
|
187 |
"Vicuna v1.5 (13B)",
|
188 |
"together_ai/lmsys/vicuna-13b-v1.5",
|
189 |
None,
|
190 |
"Together AI",
|
191 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
192 |
),
|
193 |
-
Model("Vicuna v1.5 (7B)", "together_ai/lmsys/vicuna-7b-v1.5", None, "Together AI", input_size=4096, size_billion_parameters=7, selected=True),
|
194 |
Model(
|
195 |
"Code Llama Instruct (13B)",
|
196 |
"together_ai/codellama/CodeLlama-13b-Instruct-hf",
|
197 |
None,
|
198 |
"Together AI",
|
199 |
-
|
200 |
),
|
201 |
Model(
|
202 |
"Code Llama Instruct (34B)",
|
203 |
"together_ai/codellama/CodeLlama-34b-Instruct-hf",
|
204 |
None,
|
205 |
"Together AI",
|
206 |
-
|
207 |
),
|
208 |
Model(
|
209 |
"Code Llama Instruct (70B)",
|
210 |
"together_ai/codellama/CodeLlama-70b-Instruct-hf",
|
211 |
None,
|
212 |
"Together AI",
|
213 |
-
|
214 |
),
|
215 |
Model(
|
216 |
"Code Llama Instruct (7B)",
|
@@ -218,7 +227,7 @@ MODELS = [
|
|
218 |
None,
|
219 |
"Together AI",
|
220 |
size_billion_parameters=7,
|
221 |
-
|
222 |
),
|
223 |
Model(
|
224 |
"LLaMA-2 Chat (13B)",
|
@@ -226,7 +235,7 @@ MODELS = [
|
|
226 |
None,
|
227 |
"Together AI",
|
228 |
size_billion_parameters=13,
|
229 |
-
|
230 |
),
|
231 |
Model(
|
232 |
"LLaMA-2 Chat (70B)",
|
@@ -234,7 +243,7 @@ MODELS = [
|
|
234 |
None,
|
235 |
"Together AI",
|
236 |
size_billion_parameters=70,
|
237 |
-
|
238 |
),
|
239 |
Model(
|
240 |
"LLaMA-2 Chat (7B)",
|
@@ -242,7 +251,7 @@ MODELS = [
|
|
242 |
None,
|
243 |
"Together AI",
|
244 |
size_billion_parameters=7,
|
245 |
-
|
246 |
# selected=True,
|
247 |
),
|
248 |
Model(
|
@@ -251,7 +260,7 @@ MODELS = [
|
|
251 |
None,
|
252 |
"Together AI",
|
253 |
size_billion_parameters=7,
|
254 |
-
|
255 |
),
|
256 |
Model(
|
257 |
"Mistral (7B) Instruct v0.2 (Together AI)",
|
@@ -259,7 +268,7 @@ MODELS = [
|
|
259 |
None,
|
260 |
"Together AI",
|
261 |
size_billion_parameters=7,
|
262 |
-
|
263 |
selected=True,
|
264 |
),
|
265 |
Model(
|
@@ -267,8 +276,8 @@ MODELS = [
|
|
267 |
"together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1",
|
268 |
None,
|
269 |
"Together AI",
|
270 |
-
size_billion_parameters=8*7,
|
271 |
-
|
272 |
),
|
273 |
Model(
|
274 |
"Nous Capybara v1.9 (7B)",
|
@@ -276,23 +285,23 @@ MODELS = [
|
|
276 |
None,
|
277 |
"Together AI",
|
278 |
size_billion_parameters=7,
|
279 |
-
|
280 |
),
|
281 |
Model(
|
282 |
"Nous Hermes 2 - Mixtral 8x7B-DPO (46.7B)",
|
283 |
"together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
|
284 |
None,
|
285 |
"Together AI",
|
286 |
-
size_billion_parameters=8*7,
|
287 |
-
|
288 |
),
|
289 |
Model(
|
290 |
"Nous Hermes 2 - Mixtral 8x7B-SFT (46.7B)",
|
291 |
"together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT",
|
292 |
None,
|
293 |
"Together AI",
|
294 |
-
size_billion_parameters=8*7,
|
295 |
-
|
296 |
),
|
297 |
Model(
|
298 |
"Nous Hermes LLaMA-2 (7B)",
|
@@ -300,7 +309,7 @@ MODELS = [
|
|
300 |
None,
|
301 |
"Together AI",
|
302 |
size_billion_parameters=7,
|
303 |
-
|
304 |
),
|
305 |
Model(
|
306 |
"Nous Hermes Llama-2 (13B)",
|
@@ -308,7 +317,7 @@ MODELS = [
|
|
308 |
None,
|
309 |
"Together AI",
|
310 |
size_billion_parameters=13,
|
311 |
-
|
312 |
),
|
313 |
Model(
|
314 |
"Nous Hermes-2 Yi (34B)",
|
@@ -316,7 +325,7 @@ MODELS = [
|
|
316 |
None,
|
317 |
"Together AI",
|
318 |
size_billion_parameters=34,
|
319 |
-
|
320 |
),
|
321 |
Model(
|
322 |
"OpenChat 3.5 (7B)",
|
@@ -324,7 +333,7 @@ MODELS = [
|
|
324 |
None,
|
325 |
"Together AI",
|
326 |
size_billion_parameters=7,
|
327 |
-
|
328 |
),
|
329 |
Model(
|
330 |
"OpenOrca Mistral (7B) 8K",
|
@@ -332,7 +341,7 @@ MODELS = [
|
|
332 |
None,
|
333 |
"Together AI",
|
334 |
size_billion_parameters=7,
|
335 |
-
|
336 |
),
|
337 |
Model(
|
338 |
"Qwen-Chat (7B)",
|
@@ -340,7 +349,7 @@ MODELS = [
|
|
340 |
None,
|
341 |
"Together AI",
|
342 |
size_billion_parameters=7,
|
343 |
-
|
344 |
),
|
345 |
Model(
|
346 |
"Qwen 1.5 Chat (0.5B)",
|
@@ -348,14 +357,14 @@ MODELS = [
|
|
348 |
None,
|
349 |
"Together AI",
|
350 |
size_billion_parameters=0.5,
|
351 |
-
|
352 |
),
|
353 |
Model(
|
354 |
"Qwen 1.5 Chat (1.8B)",
|
355 |
"together_ai/Qwen/Qwen1.5-1.8B-Chat",
|
356 |
None,
|
357 |
"Together AI",
|
358 |
-
|
359 |
size_billion_parameters=1.8,
|
360 |
),
|
361 |
Model(
|
@@ -364,10 +373,15 @@ MODELS = [
|
|
364 |
None,
|
365 |
"Together AI",
|
366 |
size_billion_parameters=4,
|
367 |
-
|
368 |
),
|
369 |
Model(
|
370 |
-
"Qwen 1.5 Chat (7B)",
|
|
|
|
|
|
|
|
|
|
|
371 |
# selected=True
|
372 |
),
|
373 |
Model(
|
@@ -376,21 +390,21 @@ MODELS = [
|
|
376 |
None,
|
377 |
"Together AI",
|
378 |
size_billion_parameters=14,
|
379 |
-
|
380 |
),
|
381 |
Model(
|
382 |
"Qwen 1.5 Chat (72B)",
|
383 |
"together_ai/Qwen/Qwen1.5-72B-Chat",
|
384 |
None,
|
385 |
"Together AI",
|
386 |
-
|
387 |
),
|
388 |
Model(
|
389 |
"Snorkel Mistral PairRM DPO (7B)",
|
390 |
"together_ai/snorkelai/Snorkel-Mistral-PairRM-DPO",
|
391 |
None,
|
392 |
"Together AI",
|
393 |
-
|
394 |
# selected=True,
|
395 |
),
|
396 |
Model(
|
@@ -398,21 +412,21 @@ MODELS = [
|
|
398 |
"together_ai/togethercomputer/alpaca-7b",
|
399 |
None,
|
400 |
"Together AI",
|
401 |
-
|
402 |
),
|
403 |
Model(
|
404 |
"OpenHermes-2-Mistral (7B)",
|
405 |
"teknium/OpenHermes-2-Mistral-7B",
|
406 |
None,
|
407 |
"Together AI",
|
408 |
-
|
409 |
),
|
410 |
Model(
|
411 |
"OpenHermes-2.5-Mistral (7B)",
|
412 |
"together_ai/teknium/OpenHermes-2p5-Mistral-7B",
|
413 |
None,
|
414 |
"Together AI",
|
415 |
-
|
416 |
# selected=True,
|
417 |
),
|
418 |
Model(
|
@@ -420,14 +434,14 @@ MODELS = [
|
|
420 |
"together_ai/togethercomputer/falcon-40b-instruct",
|
421 |
None,
|
422 |
"Together AI",
|
423 |
-
|
424 |
),
|
425 |
Model(
|
426 |
"Falcon Instruct (7B)",
|
427 |
"together_ai/togethercomputer/falcon-7b-instruct",
|
428 |
None,
|
429 |
"Together AI",
|
430 |
-
|
431 |
# selected=True,
|
432 |
),
|
433 |
Model(
|
@@ -435,7 +449,7 @@ MODELS = [
|
|
435 |
"together_ai/togethercomputer/Llama-2-7B-32K-Instruct",
|
436 |
None,
|
437 |
"Together AI",
|
438 |
-
|
439 |
),
|
440 |
Model(
|
441 |
"RedPajama-INCITE Chat (3B)",
|
@@ -443,14 +457,14 @@ MODELS = [
|
|
443 |
None,
|
444 |
"Together AI",
|
445 |
size_billion_parameters=3,
|
446 |
-
|
447 |
),
|
448 |
Model(
|
449 |
"RedPajama-INCITE Chat (7B)",
|
450 |
"together_ai/togethercomputer/RedPajama-INCITE-7B-Chat",
|
451 |
None,
|
452 |
"Together AI",
|
453 |
-
|
454 |
size_billion_parameters=7,
|
455 |
# selected=True,
|
456 |
),
|
@@ -459,7 +473,7 @@ MODELS = [
|
|
459 |
"together_ai/togethercomputer/StripedHyena-Nous-7B",
|
460 |
None,
|
461 |
"Together AI",
|
462 |
-
|
463 |
size_billion_parameters=7,
|
464 |
),
|
465 |
Model(
|
@@ -467,7 +481,7 @@ MODELS = [
|
|
467 |
"together_ai/Undi95/ReMM-SLERP-L2-13B",
|
468 |
None,
|
469 |
"Together AI",
|
470 |
-
|
471 |
size_billion_parameters=13,
|
472 |
),
|
473 |
Model(
|
@@ -475,15 +489,15 @@ MODELS = [
|
|
475 |
"together_ai/Undi95/Toppy-M-7B",
|
476 |
None,
|
477 |
"Together AI",
|
478 |
-
|
479 |
-
size_billion_parameters=7
|
480 |
),
|
481 |
Model(
|
482 |
"WizardLM v1.2 (13B)",
|
483 |
"together_ai/WizardLM/WizardLM-13B-V1.2",
|
484 |
None,
|
485 |
"Together AI",
|
486 |
-
|
487 |
size_billion_parameters=13,
|
488 |
# selected=True,
|
489 |
),
|
@@ -492,7 +506,7 @@ MODELS = [
|
|
492 |
"together_ai/upstage/SOLAR-10.7B-Instruct-v1.0",
|
493 |
None,
|
494 |
"Together AI",
|
495 |
-
|
496 |
size_billion_parameters=11,
|
497 |
# selected=True,
|
498 |
),
|
|
|
15 |
cost_per_million_tokens: int = None
|
16 |
cost_per_million_input_tokens: int = None
|
17 |
cost_per_million_output_tokens: int = None
|
18 |
+
context_length: int = None
|
19 |
selected: bool = False
|
20 |
|
21 |
def __post_init__(self):
|
|
|
48 |
cost_per_million_input_tokens=1,
|
49 |
cost_per_million_output_tokens=2,
|
50 |
# https://learn.microsoft.com/en-us/answers/questions/1356487/what-is-the-exact-maximum-input-tokens-of-azure-gp
|
51 |
+
context_length=4096,
|
52 |
),
|
53 |
Model(
|
54 |
"gpt-4-turbo",
|
|
|
59 |
cost_per_million_input_tokens=10,
|
60 |
cost_per_million_output_tokens=30,
|
61 |
# https://writesonic.com/blog/gpt-4-turbo-vs-gpt-4
|
62 |
+
context_length=128_000,
|
63 |
),
|
64 |
Model(
|
65 |
"gpt-4",
|
|
|
69 |
supports_functions=True,
|
70 |
cost_per_million_input_tokens=30,
|
71 |
cost_per_million_output_tokens=60,
|
72 |
+
context_length=32_000,
|
73 |
),
|
74 |
# source: https://www.together.ai/pricing
|
75 |
Model(
|
|
|
80 |
cost_per_million_tokens=0.9,
|
81 |
size_billion_parameters=70,
|
82 |
# https://github.com/facebookresearch/llama/issues/148
|
83 |
+
context_length=2048,
|
84 |
),
|
85 |
Model(
|
86 |
"Mixtral-8x7B-Instruct-v0.1",
|
|
|
106 |
"Hugging Face Inference Endpoint",
|
107 |
hourly_cost=1.30,
|
108 |
size_billion_parameters=7,
|
109 |
+
selected=True,
|
110 |
),
|
111 |
Model(
|
112 |
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
|
|
|
135 |
cost_per_million_input_tokens=0.25,
|
136 |
cost_per_million_output_tokens=0.5,
|
137 |
# https://ai.google.dev/models/palm
|
138 |
+
context_length=8196,
|
139 |
),
|
140 |
Model(
|
141 |
"chat-bison-32k (PaLM 2 32K)",
|
|
|
152 |
"together_ai/zero-one-ai/Yi-34B-Chat",
|
153 |
None,
|
154 |
"Together AI",
|
155 |
+
context_length=4096,
|
156 |
# selected=True,
|
157 |
),
|
158 |
Model(
|
|
|
160 |
"together_ai/Austism/chronos-hermes-13b",
|
161 |
None,
|
162 |
"Together AI",
|
163 |
+
context_length=2048,
|
164 |
# selected=True,
|
165 |
),
|
166 |
Model(
|
|
|
168 |
"together_ai/deepseek-ai/deepseek-coder-33b-instruct",
|
169 |
None,
|
170 |
"Together AI",
|
171 |
+
context_length=16384,
|
172 |
),
|
173 |
Model(
|
174 |
"Platypus2 Instruct (70B)",
|
175 |
"together_ai/garage-bAInd/Platypus2-70B-instruct",
|
176 |
None,
|
177 |
"Together AI",
|
178 |
+
context_length=4096,
|
179 |
),
|
180 |
Model(
|
181 |
"MythoMax-L2 (13B)",
|
182 |
"together_ai/Gryphe/MythoMax-L2-13b",
|
183 |
None,
|
184 |
"Together AI",
|
185 |
+
context_length=4096,
|
186 |
),
|
187 |
Model(
|
188 |
"Vicuna v1.5 (13B)",
|
189 |
"together_ai/lmsys/vicuna-13b-v1.5",
|
190 |
None,
|
191 |
"Together AI",
|
192 |
+
context_length=4096,
|
193 |
+
),
|
194 |
+
Model(
|
195 |
+
"Vicuna v1.5 (7B)",
|
196 |
+
"together_ai/lmsys/vicuna-7b-v1.5",
|
197 |
+
None,
|
198 |
+
"Together AI",
|
199 |
+
context_length=4096,
|
200 |
+
size_billion_parameters=7,
|
201 |
+
# selected=True
|
202 |
),
|
|
|
203 |
Model(
|
204 |
"Code Llama Instruct (13B)",
|
205 |
"together_ai/codellama/CodeLlama-13b-Instruct-hf",
|
206 |
None,
|
207 |
"Together AI",
|
208 |
+
context_length=16384,
|
209 |
),
|
210 |
Model(
|
211 |
"Code Llama Instruct (34B)",
|
212 |
"together_ai/codellama/CodeLlama-34b-Instruct-hf",
|
213 |
None,
|
214 |
"Together AI",
|
215 |
+
context_length=16384,
|
216 |
),
|
217 |
Model(
|
218 |
"Code Llama Instruct (70B)",
|
219 |
"together_ai/codellama/CodeLlama-70b-Instruct-hf",
|
220 |
None,
|
221 |
"Together AI",
|
222 |
+
context_length=4096,
|
223 |
),
|
224 |
Model(
|
225 |
"Code Llama Instruct (7B)",
|
|
|
227 |
None,
|
228 |
"Together AI",
|
229 |
size_billion_parameters=7,
|
230 |
+
context_length=16384,
|
231 |
),
|
232 |
Model(
|
233 |
"LLaMA-2 Chat (13B)",
|
|
|
235 |
None,
|
236 |
"Together AI",
|
237 |
size_billion_parameters=13,
|
238 |
+
context_length=4096,
|
239 |
),
|
240 |
Model(
|
241 |
"LLaMA-2 Chat (70B)",
|
|
|
243 |
None,
|
244 |
"Together AI",
|
245 |
size_billion_parameters=70,
|
246 |
+
context_length=4096,
|
247 |
),
|
248 |
Model(
|
249 |
"LLaMA-2 Chat (7B)",
|
|
|
251 |
None,
|
252 |
"Together AI",
|
253 |
size_billion_parameters=7,
|
254 |
+
context_length=4096,
|
255 |
# selected=True,
|
256 |
),
|
257 |
Model(
|
|
|
260 |
None,
|
261 |
"Together AI",
|
262 |
size_billion_parameters=7,
|
263 |
+
context_length=4096,
|
264 |
),
|
265 |
Model(
|
266 |
"Mistral (7B) Instruct v0.2 (Together AI)",
|
|
|
268 |
None,
|
269 |
"Together AI",
|
270 |
size_billion_parameters=7,
|
271 |
+
context_length=32768,
|
272 |
selected=True,
|
273 |
),
|
274 |
Model(
|
|
|
276 |
"together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1",
|
277 |
None,
|
278 |
"Together AI",
|
279 |
+
size_billion_parameters=8 * 7,
|
280 |
+
context_length=32768,
|
281 |
),
|
282 |
Model(
|
283 |
"Nous Capybara v1.9 (7B)",
|
|
|
285 |
None,
|
286 |
"Together AI",
|
287 |
size_billion_parameters=7,
|
288 |
+
context_length=8192,
|
289 |
),
|
290 |
Model(
|
291 |
"Nous Hermes 2 - Mixtral 8x7B-DPO (46.7B)",
|
292 |
"together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
|
293 |
None,
|
294 |
"Together AI",
|
295 |
+
size_billion_parameters=8 * 7,
|
296 |
+
context_length=32768,
|
297 |
),
|
298 |
Model(
|
299 |
"Nous Hermes 2 - Mixtral 8x7B-SFT (46.7B)",
|
300 |
"together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT",
|
301 |
None,
|
302 |
"Together AI",
|
303 |
+
size_billion_parameters=8 * 7,
|
304 |
+
context_length=32768,
|
305 |
),
|
306 |
Model(
|
307 |
"Nous Hermes LLaMA-2 (7B)",
|
|
|
309 |
None,
|
310 |
"Together AI",
|
311 |
size_billion_parameters=7,
|
312 |
+
context_length=4096,
|
313 |
),
|
314 |
Model(
|
315 |
"Nous Hermes Llama-2 (13B)",
|
|
|
317 |
None,
|
318 |
"Together AI",
|
319 |
size_billion_parameters=13,
|
320 |
+
context_length=4096,
|
321 |
),
|
322 |
Model(
|
323 |
"Nous Hermes-2 Yi (34B)",
|
|
|
325 |
None,
|
326 |
"Together AI",
|
327 |
size_billion_parameters=34,
|
328 |
+
context_length=4096,
|
329 |
),
|
330 |
Model(
|
331 |
"OpenChat 3.5 (7B)",
|
|
|
333 |
None,
|
334 |
"Together AI",
|
335 |
size_billion_parameters=7,
|
336 |
+
context_length=8192,
|
337 |
),
|
338 |
Model(
|
339 |
"OpenOrca Mistral (7B) 8K",
|
|
|
341 |
None,
|
342 |
"Together AI",
|
343 |
size_billion_parameters=7,
|
344 |
+
context_length=8192,
|
345 |
),
|
346 |
Model(
|
347 |
"Qwen-Chat (7B)",
|
|
|
349 |
None,
|
350 |
"Together AI",
|
351 |
size_billion_parameters=7,
|
352 |
+
context_length=8192,
|
353 |
),
|
354 |
Model(
|
355 |
"Qwen 1.5 Chat (0.5B)",
|
|
|
357 |
None,
|
358 |
"Together AI",
|
359 |
size_billion_parameters=0.5,
|
360 |
+
context_length=32768,
|
361 |
),
|
362 |
Model(
|
363 |
"Qwen 1.5 Chat (1.8B)",
|
364 |
"together_ai/Qwen/Qwen1.5-1.8B-Chat",
|
365 |
None,
|
366 |
"Together AI",
|
367 |
+
context_length=32768,
|
368 |
size_billion_parameters=1.8,
|
369 |
),
|
370 |
Model(
|
|
|
373 |
None,
|
374 |
"Together AI",
|
375 |
size_billion_parameters=4,
|
376 |
+
context_length=32768,
|
377 |
),
|
378 |
Model(
|
379 |
+
"Qwen 1.5 Chat (7B)",
|
380 |
+
"together_ai/Qwen/Qwen1.5-7B-Chat",
|
381 |
+
None,
|
382 |
+
"Together AI",
|
383 |
+
context_length=32768,
|
384 |
+
size_billion_parameters=7
|
385 |
# selected=True
|
386 |
),
|
387 |
Model(
|
|
|
390 |
None,
|
391 |
"Together AI",
|
392 |
size_billion_parameters=14,
|
393 |
+
context_length=32768,
|
394 |
),
|
395 |
Model(
|
396 |
"Qwen 1.5 Chat (72B)",
|
397 |
"together_ai/Qwen/Qwen1.5-72B-Chat",
|
398 |
None,
|
399 |
"Together AI",
|
400 |
+
context_length=4096,
|
401 |
),
|
402 |
Model(
|
403 |
"Snorkel Mistral PairRM DPO (7B)",
|
404 |
"together_ai/snorkelai/Snorkel-Mistral-PairRM-DPO",
|
405 |
None,
|
406 |
"Together AI",
|
407 |
+
context_length=32768,
|
408 |
# selected=True,
|
409 |
),
|
410 |
Model(
|
|
|
412 |
"together_ai/togethercomputer/alpaca-7b",
|
413 |
None,
|
414 |
"Together AI",
|
415 |
+
context_length=2048,
|
416 |
),
|
417 |
Model(
|
418 |
"OpenHermes-2-Mistral (7B)",
|
419 |
"teknium/OpenHermes-2-Mistral-7B",
|
420 |
None,
|
421 |
"Together AI",
|
422 |
+
context_length=8192,
|
423 |
),
|
424 |
Model(
|
425 |
"OpenHermes-2.5-Mistral (7B)",
|
426 |
"together_ai/teknium/OpenHermes-2p5-Mistral-7B",
|
427 |
None,
|
428 |
"Together AI",
|
429 |
+
context_length=8192,
|
430 |
# selected=True,
|
431 |
),
|
432 |
Model(
|
|
|
434 |
"together_ai/togethercomputer/falcon-40b-instruct",
|
435 |
None,
|
436 |
"Together AI",
|
437 |
+
context_length=2048,
|
438 |
),
|
439 |
Model(
|
440 |
"Falcon Instruct (7B)",
|
441 |
"together_ai/togethercomputer/falcon-7b-instruct",
|
442 |
None,
|
443 |
"Together AI",
|
444 |
+
context_length=2048,
|
445 |
# selected=True,
|
446 |
),
|
447 |
Model(
|
|
|
449 |
"together_ai/togethercomputer/Llama-2-7B-32K-Instruct",
|
450 |
None,
|
451 |
"Together AI",
|
452 |
+
context_length=32768,
|
453 |
),
|
454 |
Model(
|
455 |
"RedPajama-INCITE Chat (3B)",
|
|
|
457 |
None,
|
458 |
"Together AI",
|
459 |
size_billion_parameters=3,
|
460 |
+
context_length=2048,
|
461 |
),
|
462 |
Model(
|
463 |
"RedPajama-INCITE Chat (7B)",
|
464 |
"together_ai/togethercomputer/RedPajama-INCITE-7B-Chat",
|
465 |
None,
|
466 |
"Together AI",
|
467 |
+
context_length=2048,
|
468 |
size_billion_parameters=7,
|
469 |
# selected=True,
|
470 |
),
|
|
|
473 |
"together_ai/togethercomputer/StripedHyena-Nous-7B",
|
474 |
None,
|
475 |
"Together AI",
|
476 |
+
context_length=32768,
|
477 |
size_billion_parameters=7,
|
478 |
),
|
479 |
Model(
|
|
|
481 |
"together_ai/Undi95/ReMM-SLERP-L2-13B",
|
482 |
None,
|
483 |
"Together AI",
|
484 |
+
context_length=4096,
|
485 |
size_billion_parameters=13,
|
486 |
),
|
487 |
Model(
|
|
|
489 |
"together_ai/Undi95/Toppy-M-7B",
|
490 |
None,
|
491 |
"Together AI",
|
492 |
+
context_length=4096,
|
493 |
+
size_billion_parameters=7,
|
494 |
),
|
495 |
Model(
|
496 |
"WizardLM v1.2 (13B)",
|
497 |
"together_ai/WizardLM/WizardLM-13B-V1.2",
|
498 |
None,
|
499 |
"Together AI",
|
500 |
+
context_length=4096,
|
501 |
size_billion_parameters=13,
|
502 |
# selected=True,
|
503 |
),
|
|
|
506 |
"together_ai/upstage/SOLAR-10.7B-Instruct-v1.0",
|
507 |
None,
|
508 |
"Together AI",
|
509 |
+
context_length=4096,
|
510 |
size_billion_parameters=11,
|
511 |
# selected=True,
|
512 |
),
|