# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb. # %% auto 0 __all__ = ['columns_to_click', 'title', 'description', 'dtypes', 'get_data'] # %% app.ipynb 0 import gradio as gr import pandas as pd # %% app.ipynb 1 columns_to_click = ["Paper / Repo", "Playground"] def get_data(): # Load the CSV file into a DataFrame df = pd.read_csv( #test "https://docs.google.com/spreadsheets/d/e/2PACX-1vTmhqd7F40mODp2OeQLAn0t_IUd2tjGx0XIWt98HsKORKlejOGsrk6RP9rjjLF7k4krAkrce1FzlluT/pub?output=csv", "https://docs.google.com/spreadsheets/d/e/2PACX-1vSC40sszorOjHfozmNqJT9lFiJhG94u3fbr3Ss_7fzcU3xqqJQuW1Ie_SNcWEB-uIsBi9NBUK7-ddet/pub?output=csv", skiprows=1, ) print("df.columns: ", df.columns) # Drop rows where the 'Model' column is NaN df.dropna(subset=['Model'], inplace=True) # Drop rows where the 'Parameters \n(B)' column is 'TBA' df = df[df["Announced\n▼"] != "TBA"] # Apply make_clickable_cell to the specified columns for col in columns_to_click: df[col] = df[col].apply(make_clickable_cell) return df # %% app.ipynb 2 # Drop footers df = df.copy()[~df["Model"].isna()] # %% app.ipynb 3 # Drop TBA models df = df.copy()[df["Announced\n▼"] != "TBA"] # %% app.ipynb 6 def make_clickable_cell(cell): if pd.isnull(cell): return "" else: return f'{cell}' # Load the data to get the columns for setting up datatype dataframe = get_data() dtypes = ["str" if c not in columns_to_click else "html" for c in dataframe.columns] # %% app.ipynb 2 title = """

The Large Language Models Landscape

""" description = """Large Language Models (LLMs) today come in a variety architectures and capabilities. This interactive landscape provides a visual overview of the most important LLMs, including their training data, size, release date, and whether they are openly accessible or not. It also includes notes on each model to provide additional context. This landscape is derived from data compiled by Dr. Alan D. Thompson at [LifeArchitect.ai/models-table](https://lifearchitect.ai/models-table/). """ # %% app.ipynb 3 dtypes = ["str" if c not in columns_to_click else "markdown" for c in get_data().columns] print("dtypes: ", dtypes) # %% app.ipynb 4 with gr.Blocks() as demo: gr.Markdown(title) gr.Markdown(description) gr.DataFrame(get_data, datatype=dtypes, every=60) demo.queue().launch()