Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
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@@ -425,9 +425,53 @@ with gr.Blocks(css="""
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min-height: 90px;
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font-size: 35px;
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}
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""") as demo:
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gr.Markdown(config.ARENA_NAME)
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-
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# Leaderboard Tab (now first)
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with gr.Tab("Leaderboard"):
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min-height: 90px;
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font-size: 35px;
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}
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.sponsor-button {
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background-color: #30363D;
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color: white;
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border: none;
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padding: 10px 20px;
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border-radius: 6px;
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cursor: pointer;
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display: inline-flex;
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align-items: center;
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gap: 8px;
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font-weight: bold;
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}
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.sponsor-button:hover {
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background-color: #2D333B;
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}
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""") as demo:
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gr.Markdown(config.ARENA_NAME)
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# Main description with sponsor button
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with gr.Row():
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with gr.Column(scale=8):
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gr.Markdown("""
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**Step right up to the arena where frugal meets fabulous in the world of AI!**
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Watch as our compact contenders (maxing out at 14B parameters) duke it out in a battle of wits and words.
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What started as a simple experiment has grown into a popular platform for evaluating compact language models.
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As the arena continues to expand with more models, features, and battles, it requires computational resources to maintain and improve.
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If you find this project valuable and would like to support its development, consider sponsoring:
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""")
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with gr.Column(scale=2):
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gr.Button(
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"Sponsor on GitHub",
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link="https://github.com/sponsors/k-mktr",
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elem_classes="sponsor-button"
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)
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# Instructions in an accordion
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with gr.Accordion("📖 How to Use", open=False):
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gr.Markdown("""
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1. To start the battle, go to the 'Battle Arena' tab.
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2. Type your prompt into the text box. Alternatively, click the "🎲" button to receive a random prompt.
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3. Click the "Generate Responses" button to view the models' responses.
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4. Cast your vote for the model that provided the better response. In the event of a Tie, enter a new prompt before continuing the battle.
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5. Check out the Leaderboard to see how models rank against each other.
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More info: [README.md](https://huggingface.co/spaces/k-mktr/gpu-poor-llm-arena/blob/main/README.md)
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""")
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# Leaderboard Tab (now first)
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with gr.Tab("Leaderboard"):
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