Spaces:
Running
Running
BenchmarkBot
commited on
Commit
β’
0eea6c1
1
Parent(s):
8e785e9
fix search bar
Browse files- app.py +25 -2
- src/assets/text_content.py +1 -1
app.py
CHANGED
@@ -1,11 +1,12 @@
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import os
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import gradio as gr
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import pandas as pd
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from apscheduler.schedulers.background import BackgroundScheduler
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from src.assets.text_content import TITLE, INTRODUCTION_TEXT, CITATION_BUTTON_LABEL, CITATION_BUTTON_TEXT
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from src.assets.css_html_js import custom_css
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from src.utils import restart_space, load_dataset_repo, make_clickable_model
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LLM_PERF_LEADERBOARD_REPO = "optimum/llm-perf-leaderboard"
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@@ -45,8 +46,22 @@ def get_benchmark_df(benchmark):
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return df
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def search_table(df, query):
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filtered_df = df[df["
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return filtered_df
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@@ -132,6 +147,14 @@ with demo:
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elem_id="citation-button",
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).style(show_copy_button=True)
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# Restart space every hour
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scheduler = BackgroundScheduler()
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scheduler.add_job(restart_space, "interval", seconds=3600,
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import os
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import json
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import gradio as gr
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import pandas as pd
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from apscheduler.schedulers.background import BackgroundScheduler
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from src.assets.text_content import TITLE, INTRODUCTION_TEXT, CITATION_BUTTON_LABEL, CITATION_BUTTON_TEXT
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from src.utils import restart_space, load_dataset_repo, make_clickable_model
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from src.assets.css_html_js import custom_css, get_window_url_params
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LLM_PERF_LEADERBOARD_REPO = "optimum/llm-perf-leaderboard"
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return df
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def change_tab(query_param):
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query_param = query_param.replace("'", '"')
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query_param = json.loads(query_param)
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if (
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isinstance(query_param, dict)
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and "tab" in query_param
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and query_param["tab"] == "evaluation"
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):
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return gr.Tabs.update(selected=1)
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else:
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return gr.Tabs.update(selected=0)
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def search_table(df, query):
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filtered_df = df[df["Model π€"].str.contains(query, case=False)]
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return filtered_df
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elem_id="citation-button",
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).style(show_copy_button=True)
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dummy = gr.Textbox(visible=False)
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demo.load(
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change_tab,
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dummy,
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tabs,
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_js=get_window_url_params,
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)
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# Restart space every hour
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scheduler = BackgroundScheduler()
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scheduler.add_job(restart_space, "interval", seconds=3600,
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src/assets/text_content.py
CHANGED
@@ -4,7 +4,7 @@ INTRODUCTION_TEXT = f"""
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The π€ Open LLM-Perf Leaderboard ποΈ aims to benchmark the performance (latency & throughput) of Large Language Models (LLMs) on different hardwares and backends using [Optimum-Benchmark](https://github.com/huggingface/optimum-benchmark) and [Optimum](https://github.com/huggingface/optimum) flavors.
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Anyone from the community can submit a model or a hardware+backend configuration for automated benchmarking:
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- Model submissions should be made in the [π€ Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) and will be added to the π€ Open LLM-Perf Leaderboard ποΈ once they're publicly available.
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- Hardware+Backend submissions should be made in the π€ Open LLM-Perf Leaderboard ποΈ [community discussions](https://huggingface.co/spaces/optimum/llm-perf-leaderboard/discussions); An automated process will be set up soon
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[Config files](https://github.com/huggingface/optimum-benchmark/blob/main/examples/bert.yaml) (which can be used with Optimum-Benchmark) will be available soon for reproduction and questioning/correction of the results.
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"""
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The π€ Open LLM-Perf Leaderboard ποΈ aims to benchmark the performance (latency & throughput) of Large Language Models (LLMs) on different hardwares and backends using [Optimum-Benchmark](https://github.com/huggingface/optimum-benchmark) and [Optimum](https://github.com/huggingface/optimum) flavors.
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Anyone from the community can submit a model or a hardware+backend configuration for automated benchmarking:
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- Model submissions should be made in the [π€ Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) and will be added to the π€ Open LLM-Perf Leaderboard ποΈ once they're publicly available.
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- Hardware+Backend submissions should be made in the π€ Open LLM-Perf Leaderboard ποΈ [community discussions](https://huggingface.co/spaces/optimum/llm-perf-leaderboard/discussions); An automated process will be set up soon.
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[Config files](https://github.com/huggingface/optimum-benchmark/blob/main/examples/bert.yaml) (which can be used with Optimum-Benchmark) will be available soon for reproduction and questioning/correction of the results.
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"""
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