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Update app.py
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app.py
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@@ -1,11 +1,14 @@
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import os
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import sys
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import time
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import random
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import yaml
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import subprocess
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import runpod
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import gradio as gr
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import pandas as pd
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from jinja2 import Template
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@@ -303,6 +306,39 @@ def create_pod(model_name: str, username: str, n=10, wait_seconds=10):
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print("All attempts failed. Giving up.")
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raise
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def merge_loop():
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# Start HF API
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api = HfApi(token=HF_TOKEN)
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@@ -366,11 +402,14 @@ title = """
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<p><em>AutoMerger selects two 7B models on top of the Open LLM Leaderboard, combine them with a merge technique, and evaluate the resulting model.</em></p>
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</div>
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"""
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with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
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gr.Markdown(title)
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logs = gr.Textbox(label="Logs")
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demo.load(read_logs, None, logs, every=1)
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-
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print("Start AutoMerger...")
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import os
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import re
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import sys
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import time
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import random
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import yaml
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import subprocess
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from io import StringIO
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import runpod
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import requests
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import gradio as gr
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import pandas as pd
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from jinja2 import Template
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print("All attempts failed. Giving up.")
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raise
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def download_leaderboard():
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url = "https://gist.githubusercontent.com/automerger/84af749b1c0ef7336858df408f46f388/raw"
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file_path = "leaderboard.txt"
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response = requests.get(url)
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return response.content.decode('utf-8')
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def convert_markdown_table_to_dataframe(md_content):
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"""
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Converts markdown table to Pandas DataFrame.
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"""
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# Remove leading and trailing | characters
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cleaned_content = re.sub(r'\|\s*$', '', re.sub(r'^\|\s*', '', md_content, flags=re.MULTILINE), flags=re.MULTILINE)
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# Create DataFrame from cleaned content
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df = pd.read_csv(StringIO(cleaned_content), sep="\|", engine='python')
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# Remove the first row after the header
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df = df.drop(0, axis=0)
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# Strip whitespace from column names
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df.columns = df.columns.str.strip()
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return df
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def get_dataframe():
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content = download_leaderboard()
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df = convert_markdown_table_to_dataframe(content)
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return df
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def merge_loop():
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# Start HF API
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api = HfApi(token=HF_TOKEN)
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<p><em>AutoMerger selects two 7B models on top of the Open LLM Leaderboard, combine them with a merge technique, and evaluate the resulting model.</em></p>
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</div>
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"""
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footer = '<div align="center"><p><em>Special thanks to <a href="https://huggingface.co/Weyaxi">Weyaxi</a> for the <a href="https://github.com/Weyaxi/scrape-open-llm-leaderboard">Open LLM Leaderboard Scraper</a> and <a href="https://github.com/cg123">Charles Goddard</a> for <a href="https://github.com/arcee-ai/mergekit">mergekit</a>.</em></p></div>'
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with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as demo:
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gr.Markdown(title)
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logs = gr.Textbox(label="Logs")
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demo.load(read_logs, None, logs, every=1)
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leaderboard = gr.Dataframe(value=get_dataframe, datatype=["markdown", "number", "number", "number", "number", "number"], every=3600)
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gr.Markdown(footer)
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demo.queue().launch(server_name="0.0.0.0", show_error=True, prevent_thread_lock=True)
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print("Start AutoMerger...")
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