clem-leaderboard / src /assets /text_content.py
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adapt short model names
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TITLE = """<h1 align="center" id="space-title"> 🏆 CLEM Leaderboard</h1>"""
INTRODUCTION_TEXT = """
The CLEM Leaderboard aims to track, rank and evaluate current cLLMs (chat-optimized Large Language Models) with the suggested pronounciation “clems”.
The benchmarking approach is described in [Clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents](https://arxiv.org/abs/2305.13455).
[Github repo](https://github.com/clembench/clembench)
"""
SHORT_NAMES = {
"t0.0": "",
"claude-v1.3": "cl-1.3",
"claude-2": "cl-2",
"claude-2.1": "cl-2.1",
"claude-instant-1.2": "cl-ins-1.2",
"gpt-3.5-turbo-0613": "3.5-0613",
"gpt-3.5-turbo-1106": "3.5-1106",
"gpt-4-0613": "4-0613",
"gpt-4-1106-preview": "4-1106",
"gpt-4-0314": "4-0314",
"gpt-4": "4",
"text-davinci-003": "3",
"luminous-supreme": "lm",
"koala-13b": "ko",
"falcon-40b": "flc",
"falcon-7b-instruct": "fal-7b",
"falcon-40b-instruct": "flc-i-40b",
"oasst-12b": "oas-12b",
"oasst-sft-4-pythia-12b-epoch-3.5": "ost-12b",
"vicuna-13b": "vic-13b",
"vicuna-33b-v1.3": "vic-33b",
"sheep-duck-llama-2-70b-v1.1": "sd-l2-70b",
"sheep-duck-llama-2-13b": "sd-l2-13b",
"WizardLM-70b-v1.0": "w-70b",
"CodeLlama-34b-Instruct-hf": "cl-34b",
"command": "com",
"Mistral-7B-Instruct-v0.1": "m-i-7b",
"Wizard-Vicuna-13B-Uncensored-HF": "vcn-13b",
"llama-2-13b-chat-hf": "l2-13b",
"llama-2-70b-chat-hf": "l2-70b",
"llama-2-7b-chat-hf": "l2-7b",
"koala-13B-HF": "k-13b"
}