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Update config.py
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config.py
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@@ -5,15 +5,27 @@ from datetime import datetime
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import time
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import threading
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ARENA_NAME = "# π The GPU-Poor LLM Gladiator Arena π"
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ARENA_DESCRIPTION = """
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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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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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# Ollama API configuration
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import time
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import threading
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ARENA_NAME = "# π The GPU-Poor LLM Gladiator Arena π v25.03"
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ARENA_DESCRIPTION = """
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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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[](https://github.com/sponsors/k-mktr)
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<details>
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<summary>π How to Use</summary>
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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 "π²" 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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</details>
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"""
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# Ollama API configuration
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