Simon Pagezy

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155
Hello Hugging Face Community,

if you use Google Kubernetes Engine to host you ML workloads, I think this series of videos is a great way to kickstart your journey of deploying LLMs, in less than 10 minutes! Thank you @wietse-venema-demo !

To watch in this order:
1. Learn what are Hugging Face Deep Learning Containers
https://youtu.be/aWMp_hUUa0c?si=t-LPRkRNfD3DDNfr

2. Learn how to deploy a LLM with our Deep Learning Container using Text Generation Inference
https://youtu.be/Q3oyTOU1TMc?si=V6Dv-U1jt1SR97fj

3. Learn how to scale your inference endpoint based on traffic
https://youtu.be/QjLZ5eteDds?si=nDIAirh1r6h2dQMD

If you want more of these small tutorials and have any theme in mind, let me know!
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1346
Hello Hugging Face Community,

I'd like to share here a bit more about our Deep Learning Containers (DLCs) we built with Google Cloud, to transform the way you build AI with open models on this platform!

With pre-configured, optimized environments for PyTorch Training (GPU) and Inference (CPU/GPU), Text Generation Inference (GPU), and Text Embeddings Inference (CPU/GPU), the Hugging Face DLCs offer:

⚑ Optimized performance on Google Cloud's infrastructure, with TGI, TEI, and PyTorch acceleration.
πŸ› οΈ Hassle-free environment setup, no more dependency issues.
πŸ”„ Seamless updates to the latest stable versions.
πŸ’Ό Streamlined workflow, reducing dev and maintenance overheads.
πŸ”’ Robust security features of Google Cloud.
☁️ Fine-tuned for optimal performance, integrated with GKE and Vertex AI.
πŸ“¦ Community examples for easy experimentation and implementation.
πŸ”œ TPU support for PyTorch Training/Inference and Text Generation Inference is coming soon!

Find the documentation at https://huggingface.co/docs/google-cloud/en/index
If you need support, open a conversation on the forum: https://discuss.huggingface.co/c/google-cloud/69

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