llm-perf-leaderboard / src /assets /text_content.py
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TITLE = """<h1 align="center" id="space-title">πŸ€— Open LLM-Perf Leaderboard πŸ‹οΈ</h1>"""
INTRODUCTION_TEXT = f"""
The πŸ€— Open LLM-Perf Leaderboard πŸ‹οΈ 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.
Anyone from the community can submit a model or a hardware+backend configuration for automated benchmarking:
- Model submissions should be made in the [πŸ€— Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) and will be added to the πŸ€— Open LLM-Perf Leaderboard πŸ‹οΈ once they're publicly available.
- Hardware+Backend submissions should be made in the πŸ€— Open LLM-Perf Leaderboard πŸ‹οΈ [community discussions](https://huggingface.co/spaces/optimum/llm-perf-leaderboard/discussions); An automated process will be set up soon.
[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.
"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results."
CITATION_BUTTON_TEXT = r"""@misc{open-llm-perf-leaderboard,
author = {Ilyas Moutawwakil},
title = {Open LLM-Perf Leaderboard},
year = {2023},
publisher = {Hugging Face},
howpublished = "\url{https://huggingface.co/spaces/optimum/llm-perf-leaderboard}",
@software{optimum-benchmark,
author = {Ilyas Moutawwakil},
publisher = {Hugging Face},
title = {A framework for benchmarking the performance of Transformers models on different hardwares and backends},
}
"""