-
Notifications
You must be signed in to change notification settings - Fork 932
google cloud #3166
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Merged
Merged
google cloud #3166
Changes from all commits
Commits
Show all changes
17 commits
Select commit
Hold shift + click to select a range
3f3ede8
Add announcement for partnership with Google Cloud
jeffboudier 9d1e3e3
Create new folder for blog thumbnail
jeffboudier cd2f2a7
blog post thumbnail
jeffboudier c601921
Update thumbnail for Google Cloud partnership post
jeffboudier b0caee0
Adding blog post images
jeffboudier c8c867c
Add Google Cloud partnership announcement blog
jeffboudier 23de988
Update _blog.yml
pagezyhf 42c6c51
Update google-cloud.md
pagezyhf ba6501f
Update google-cloud.md
pagezyhf 143f5fa
Update google-cloud.md
pagezyhf 2f29ed3
remove .gitkeep
pagezyhf 72dda0c
Update google-cloud.md
pagezyhf 93d3bc8
Update google-cloud.md
pagezyhf d46e7e0
Update google-cloud.md
pagezyhf 592fa6f
Update google-cloud.md
pagezyhf b6c44c7
add note to previous blog
pagezyhf 7fedb26
merge
pagezyhf File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| --- | ||
| title: "Building for an Open Future - our new partnership with Google Cloud" | ||
| thumbnail: /blog/assets/google-cloud/google-cloud-thumbnail.png | ||
| authors: | ||
| - user: jeffboudier | ||
| - user: pagezyhf | ||
| --- | ||
|
|
||
| # Building for an Open Future - our new partnership with Google Cloud | ||
|
|
||
| <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/google-cloud/google%20cloud%20blogpost%20title.png"> | ||
|
|
||
| Today, we are happy to announce a new and deeper partnership with Google Cloud, to enable companies to build their own AI with open models. | ||
|
|
||
| “_Google has made some of the most impactful contributions to open AI, from the OG transformer to the Gemma models. I believe in a future where all companies will build and customize their own AI. With this new strategic partnership, we’re making it easy to do on Google Cloud._” says Jeff Boudier, at Hugging Face. | ||
|
|
||
| “_Hugging Face has been the driving force enabling companies large and small all over the world to access, use and customize now more than 2 million open models, and we’ve been proud to contribute over 1,000 of our models to the community_”, says Ryan J. Salva, Senior Director of Product Management at Google Cloud. “_Together we will make Google Cloud the best place to build with open models._” | ||
|
|
||
| ## A Partnership for Google Cloud customers | ||
|
|
||
| Google Cloud customers use open models from Hugging Face in many of its leading AI services. In Vertex AI, the most popular open models are ready to deploy in a couple clicks within Model Garden. Customers who want greater control over their AI infrastructure can find a similar model library available in GKE AI/ML, or use pre-configured environments maintained by Hugging Face. Customers also run AI inference workloads with Cloud Run GPUs, enabling serverless open model deployments. | ||
|
|
||
| The common thread: we work with Google Cloud to build seamless experiences fully leveraging the unique capabilities of each service to offer choice to the customers. | ||
pagezyhf marked this conversation as resolved.
Show resolved
Hide resolved
|
||
|
|
||
| <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/google-cloud/google-cloud-partnership.png"> | ||
|
|
||
| ## The Gateway to Open Models - A Fast Lane for Google Cloud Customers | ||
|
|
||
| Usage of Hugging Face by Google Cloud customers has grown 10x over the last 3 years, and today, this translates into tens of petabytes of model downloads every month, in billions of requests. | ||
|
|
||
| To make sure Google Cloud customers have the best experience building with models and datasets from Hugging Face, we are working together to create a CDN Gateway for Hugging Face repositories built on top of both Hugging Face Xet optimized storage and data transfer technologies, and Google Cloud advanced storage and networking capabilities. | ||
|
|
||
| This CDN Gateway will cache Hugging Face models and datasets directly on Google Cloud to significantly reduce downloading times, and strengthen model supply chain robustness for Google Cloud customers. Whether you’re using Vertex, GKE, Cloud Run or just building your own stack in VMs in Compute Engine, you will benefit from faster time-to-first-token and simplified model governance. | ||
|
|
||
| ## A partnership for Hugging Face customers | ||
|
|
||
| Hugging Face [Inference Endpoints](https://endpoints.huggingface.co/) is the easiest way to go from model to deployment in just a couple clicks. Through this deepened partnership we will bring the unique capabilities and cost performance of Google Cloud to Hugging Face customers, starting with Inference Endpoints. Expect more and newer instances available as well as price drops! | ||
|
|
||
| <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/google-cloud/inference-endpoints-google-cloud.png"> | ||
|
|
||
| We will ensure all the fruits of our product and engineering collaboration become easily available to the 10 million AI Builders on Hugging Face. Going from a model page to deploying on Vertex Model Garden or GKE should only take a couple steps. Taking a private model securely hosted in an Enterprise organization on Hugging Face should be as easy as working with public models. | ||
|
|
||
| TPUs, Google custom AI accelerator chips now in their seventh generation, have been steadily improving in performance and software stack maturity. We want to make sure Hugging Face users can fully benefit from the current and the next generations of TPUs when they build AI with open models. We are excited to make TPUs as easy to use as GPUs for Hugging Face models, thanks to native support in our libraries. | ||
|
|
||
| Additionally, this new partnership will enable Hugging Face to leverage Google industry-leading security technology to make the millions of open models on Hugging Face more secure. Powered by [Google Threat Intelligence](https://cloud.google.com/security/products/threat-intelligence) and [Mandiant](https://www.mandiant.com/), this joint effort aims to secure models, datasets and Spaces as you use the Hugging Face Hub daily. | ||
|
Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. mention virustotal as well?
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I added in a new PR |
||
|
|
||
| ## Building the open future of AI together | ||
|
|
||
| We want to see a future where every company can build their own AI with open models and host it within their own secure infrastructure, with full control. We are excited to make this future happen with Google Cloud. Our deep collaboration will accelerate this vision, whether you are using Vertex AI Model Garden, Google Kubernetes Engine, Cloud Run or Hugging Face Inference Endpoints. | ||
|
|
||
| Is there something you want us to create or improve thanks to our partnership with Google? Let us know in the comments! | ||
|
|
||
| <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/blog/google-cloud/mcface-billion-model-served-compressed.png"> | ||
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Uh oh!
There was an error while loading. Please reload this page.