Buckets:
| # Resources | |
| Take a look at our published blog posts, videos, tutorials and examples along with external relevant documentation for additional help and more context about Hugging Face on AWS. | |
| Feel free to reach out on our [community forum](https://discuss.huggingface.co/c/sagemaker/17) if you have any questions. | |
| ## Tutorials | |
| - [All tutorials](https://huggingface.co/docs/sagemaker/main/en/tutorials/introduction) | |
| ## Examples | |
| - [All examples](https://huggingface.co/docs/sagemaker/main/en/examples/introduction) | |
| ## Hugging Face Blogs | |
| - [Deploy Hugging Face models easily with Amazon SageMaker](https://huggingface.co/blog/deploy-hugging-face-models-easily-with-amazon-sagemaker) | |
| - [Hugging Face and AWS partner to make AI more accessible](https://huggingface.co/blog/aws-partnership) | |
| - [Introducing the Hugging Face LLM Inference Container for Amazon SageMaker](https://huggingface.co/blog/sagemaker-huggingface-llm) | |
| - [Hugging Face Text Generation Inference available for AWS Inferentia2](https://huggingface.co/blog/text-generation-inference-on-inferentia2) | |
| - [Subscribe to Enterprise Hub with your AWS Account](https://huggingface.co/blog/enterprise-hub-aws-marketplace) | |
| - [Deploy models on AWS Inferentia2 from Hugging Face](https://huggingface.co/blog/inferentia-inference-endpoints) | |
| - [Introducing the Hugging Face Embedding Container for Amazon SageMaker](https://huggingface.co/blog/sagemaker-huggingface-embedding) | |
| - [Use Hugging Face models with Amazon Bedrock](https://huggingface.co/blog/bedrock-marketplace) | |
| ## AWS Blogs | |
| - [AWS: Embracing natural language processing with Hugging Face](https://aws.amazon.com/de/blogs/opensource/embracing-natural-language-processing-with-hugging-face/) | |
| - [AWS and Hugging Face collaborate to simplify and accelerate adoption of natural language processing models](https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/) | |
| - [AWS and Hugging Face collaborate to make generative AI more accessible and cost efficient](https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-make-generative-ai-more-accessible-and-cost-efficient/) | |
| - [Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models](https://aws.amazon.com/blogs/machine-learning/use-amazon-bedrock-tooling-with-amazon-sagemaker-jumpstart-models/) | |
| - [Deploy RAG applications on Amazon SageMaker JumpStart using FAISS](https://aws.amazon.com/blogs/machine-learning/deploy-rag-applications-on-amazon-sagemaker-jumpstart-using-faiss/) | |
| - [Fine-tune and host SDXL models cost-effectively with AWS Inferentia2](https://aws.amazon.com/blogs/machine-learning/fine-tune-and-host-sdxl-models-cost-effectively-with-aws-inferentia2/) | |
| - [Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI](https://aws.amazon.com/blogs/machine-learning/achieve-2x-speed-up-in-llm-inference-with-medusa-1-on-amazon-sagemaker-ai/) | |
| - [Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI](https://aws.amazon.com/blogs/machine-learning/optimize-hosting-deepseek-r1-distilled-models-with-hugging-face-tgi-on-amazon-sagemaker-ai/) | |
| ## Videos | |
| - [Walkthrough: End-to-End Text Classification](https://youtu.be/ok3hetb42gU) | |
| - [Working with Hugging Face models on Amazon SageMaker](https://youtu.be/leyrCgLAGjMn) | |
| - [Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker](https://youtu.be/pfBGgSGnYLs) | |
| - [Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker](https://youtu.be/l9QZuazbzWM) | |
| - [Training with Hugging Face on Amazon SageMaker](https://www.youtube.com/watch?v=BqQ14SZ5tos) | |
| - [Hosting with Hugging Face on Amazon SageMaker](https://www.youtube.com/watch?v=oVIvXfeunv8) | |
| - [Introduction to Hugging Face on Amazon SageMaker](https://www.youtu.be/watch?v=80ix-IyNnQI) | |
| ## External Documentation | |
| - [Hugging Face on AWS](https://aws.amazon.com/ai/hugging-face/) | |
| - [Amazon SageMaker documentation for Hugging Face](https://docs.aws.amazon.com/sagemaker/latest/dg/hugging-face.html) | |
| - [Python SDK SageMaker documentation for Hugging Face](https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/index.html) | |
| - [Deep Learning Container](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers) | |
| - [LLM Hosting Container](https://github.com/awslabs/llm-hosting-container) | |
| ## Workshops | |
| - [Enterprise-Scale NLP with Hugging Face & Amazon SageMaker](https://github.com/philschmid/huggingface-sagemaker-workshop-series/tree/main) | |
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