Buckets:
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examples</a></li>',J,A,N,x,fe='<li><a href="https://huggingface.co/blog/deploy-hugging-face-models-easily-with-amazon-sagemaker" rel="nofollow">Deploy Hugging Face models easily with Amazon SageMaker</a></li> <li><a href="https://huggingface.co/blog/aws-partnership" rel="nofollow">Hugging Face and AWS partner to make AI more accessible</a></li> <li><a href="https://huggingface.co/blog/sagemaker-huggingface-llm" rel="nofollow">Introducing the Hugging Face LLM Inference Container for Amazon SageMaker</a></li> <li><a href="https://huggingface.co/blog/text-generation-inference-on-inferentia2" rel="nofollow">Hugging Face Text Generation Inference available for AWS Inferentia2</a></li> <li><a href="https://huggingface.co/blog/enterprise-hub-aws-marketplace" rel="nofollow">Subscribe to Enterprise Hub with your AWS Account</a></li> <li><a href="https://huggingface.co/blog/inferentia-inference-endpoints" rel="nofollow">Deploy models on AWS Inferentia2 from Hugging Face</a></li> <li><a href="https://huggingface.co/blog/sagemaker-huggingface-embedding" rel="nofollow">Introducing the Hugging Face Embedding Container for Amazon SageMaker</a></li> <li><a href="https://huggingface.co/blog/bedrock-marketplace" rel="nofollow">Use Hugging Face models with Amazon Bedrock</a></li>',O,z,X,L,ue='<li><a href="https://aws.amazon.com/de/blogs/opensource/embracing-natural-language-processing-with-hugging-face/" rel="nofollow">AWS: Embracing natural language processing with Hugging Face</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/" rel="nofollow">AWS and Hugging Face collaborate to simplify and accelerate adoption of natural language processing models</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-make-generative-ai-more-accessible-and-cost-efficient/" rel="nofollow">AWS and Hugging Face collaborate to make generative AI more accessible and cost efficient</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/use-amazon-bedrock-tooling-with-amazon-sagemaker-jumpstart-models/" rel="nofollow">Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/deploy-rag-applications-on-amazon-sagemaker-jumpstart-using-faiss/" rel="nofollow">Deploy RAG applications on Amazon SageMaker JumpStart using FAISS</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/fine-tune-and-host-sdxl-models-cost-effectively-with-aws-inferentia2/" rel="nofollow">Fine-tune and host SDXL models cost-effectively with AWS Inferentia2</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/achieve-2x-speed-up-in-llm-inference-with-medusa-1-on-amazon-sagemaker-ai/" rel="nofollow">Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI</a></li> <li><a href="https://aws.amazon.com/blogs/machine-learning/optimize-hosting-deepseek-r1-distilled-models-with-hugging-face-tgi-on-amazon-sagemaker-ai/" rel="nofollow">Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI</a></li>',Z,T,K,y,ce='<li><a href="https://youtu.be/ok3hetb42gU" rel="nofollow">Walkthrough: End-to-End Text Classification</a></li> <li><a href="https://youtu.be/leyrCgLAGjMn" rel="nofollow">Working with Hugging Face models on Amazon SageMaker</a></li> <li><a href="https://youtu.be/pfBGgSGnYLs" rel="nofollow">Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker</a></li> <li><a href="https://youtu.be/l9QZuazbzWM" rel="nofollow">Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker</a></li> <li><a href="https://www.youtube.com/watch?v=BqQ14SZ5tos" rel="nofollow">Training with Hugging Face on Amazon SageMaker</a></li> <li><a href="https://www.youtube.com/watch?v=oVIvXfeunv8" rel="nofollow">Hosting with Hugging Face on Amazon SageMaker</a></li> <li><a href="https://www.youtu.be/watch?v=80ix-IyNnQI" rel="nofollow">Introduction to Hugging Face on Amazon SageMaker</a></li>',Y,F,ee,_,he='<li><a href="https://aws.amazon.com/ai/hugging-face/" rel="nofollow">Hugging Face on AWS</a></li> <li><a href="https://docs.aws.amazon.com/sagemaker/latest/dg/hugging-face.html" rel="nofollow">Amazon SageMaker documentation for Hugging Face</a></li> <li><a href="https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/index.html" rel="nofollow">Python SDK SageMaker documentation for Hugging Face</a></li> <li><a href="https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers" rel="nofollow">Deep Learning Container</a></li> <li><a href="https://github.com/awslabs/llm-hosting-container" rel="nofollow">LLM Hosting Container</a></li>',te,C,ae,I,pe='<li><a href="https://github.com/philschmid/huggingface-sagemaker-workshop-series/tree/main" 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Xet Storage Details
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- d590b5a19ff8969b34b3cd911bd85cc35d9dfddd97799ee22bcdcdd9be426af6
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