GPU-Poor no more: super excited to officially release ZeroGPU in beta today. Congrats Charles, Victor & team for the release!
In the past few months, the open-source AI community has been thriving. Not only Meta but also Apple, NVIDIA, Bytedance, Snowflake, Databricks, Microsoft, Google, and more have released open models and datasets on Hugging Face, which now hosts over 1M models on the Hub which have been downloaded over a billion times. More than that, many are starting to be better than proprietary APIs.
This movement has been supported not only by big tech but also by a thriving open-source AI community that includes academic labs, startups, and independent hobbyists. For example, more than 35,000 variation models of Llama have been shared on Hugging Face since Meta’s first version a year ago—including more than 7,000 based on Llama-3—ranging from quantized and merged models to specialized models in biology and Mandarin, to name a few. More than 4 million AI builders are now using Hugging Face.
However, the open-source community doesn’t have the same resources available to train and demo these models that big tech have at their disposal, which is why ChatGPT remains the most used AI application today.
Hugging Face is fighting this by launching ZeroGPU, a shared infrastructure for indie and academic AI builders to run AI demos on Spaces, giving them the freedom to pursue their work without the financial burden of compute costs. Spaces have been the most popular way to build AI demos, with over 300,000 AI demos created so far on CPU or paid GPU (and a thousand more every day). To foster the continued development of the AI ecosystem, Hugging Face is committing $10M of free GPUs with the launch today of ZeroGPU.
Technically speaking, ZeroGPU leverages Hugging Face's experience in hosting and serving more than 100 Petabytes monthly from the Hugging Face Hub. ZeroGPU allows Spaces to run on multiple GPUs by making Spaces efficiently hold and release GPUs as needed (as opposed to a classical GPU Space that holds exactly one GPU at any time). This architecture is also more energy-efficient since GPUs are shared rather than duplicated. ZeroGPU uses NVIDIA A100 GPU devices under the hood.
You can learn more about ZeroGPU here: https://lnkd.in/e9_XhhaW
More than 1,300 ZeroGPU spaces have been built since we started giving early access to AI builders on May 1, 2024: https://lnkd.in/em-V66t6
You can find the article from @kyliebytes: https://lnkd.in/eHYUEwjZ
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