added submissions protocol

app.py

@@ -58,14 +58,8 @@ with demo:
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
 
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
-        with gr.TabItem("A100 Benchmark", elem_id="a100-benchmark", id=0):
-            A100_text = "<h1>Machine: 4x A100 80GB<h1>"
-            gr.HTML(A100_text)
-
-            dataframe_text = """
-            <h3>Batch Size: 1</h3>
-            <h3>Generated Tokens: 100</h3>
-            """
+        with gr.TabItem("4xA100-80GB Benchmark", elem_id="a100-benchmark", id=0):
+            dataframe_text = "<h4>Batch Size: 1 ; Generated Tokens: 100</h4>"
 
             gr.HTML(dataframe_text)
             benchmark_df = get_benchmark_df()

src/assets/text_content.py

@@ -3,5 +3,7 @@ TITLE = """<h1 align="center" id="space-title">🤗 Open LLM-Perf Leaderboard</h
 INTRODUCTION_TEXT = f"""
 The 🤗 Open LLM-Perf Leaderboard aims to benchmark the performance (latency & throughput) of Large Language Models (LLMs) on different backends and hardwares using [Optimum-Benchmark](https://github.com/huggingface/optimum-benchmark)
 
-🤗 Anyone from the community can submit a model for automated benchmarking on the 🤗 GPU cluster, as long as it is a 🤗 Transformers model with weights on the Hub. We also support benchmarks of models with delta-weights for non-commercial licensed models, such as LLaMa.
+🤗 Anyone from the community can submit a model or hardware+backend configuration for automated benchmarking on the 🤗 GPU cluster.
+Model submissions should be made in the [🤗 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
+Hardware+Backend submissions should be made in the [🤗 Open LLM-Perf Leaderboard's community discussions](https://huggingface.co/spaces/optimum/llm-perf-leaderboard/discussions).
 """