Panel on Hugging Face

We are thrilled to announce the collaboration between Panel and Hugging Face! 🎉 We have integrated a Panel template in Hugging Face Spaces to help you get started building Panel apps and deploy them on Hugging Face effortlessly.

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What’s going on with the Open LLM Leaderboard?

Recently an interesting discussion arose on Twitter following the release of Falcon 🦅 and its addition to the Open LLM Leaderboard, a public leaderboard comparing open access large language models. The discussion centered around one of the four evaluations displayed on the leaderboard: a benchmark for measuring Massive Multitask Language Understanding (shortname: MMLU). The community was surprised that MMLU evaluation numbers of the current top model on the leaderboard, the LLaMA model 🦙, were significantly lower than the numbers in […]

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Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2

Update (29/08/2023): A benchmark on H100 was added to this blog post. Also, all performance numbers have been updated with newer versions of software. Optimum Habana v1.7 on Habana Gaudi2 achieves x2.5 speedups compared to A100 and x1.4 compared to H100 when fine-tuning BridgeTower, a state-of-the-art vision-language model. This performance improvement relies on hardware-accelerated data loading to make the    

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Deploy LLMs with Hugging Face Inference Endpoints

Open-source LLMs like Falcon, (Open-)LLaMA, X-Gen, StarCoder or RedPajama, have come a long way in recent months and can compete with closed-source models like ChatGPT or GPT4 for certain use cases. However, deploying these models in an efficient and optimized way still presents a challenge. In this blog post, we will show you how to deploy open-source    

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