test

Author: pagezyhf

docs/sagemaker/resources.md

@@ -12,28 +12,47 @@ Feel free to reach out on our [community forum](https://discuss.huggingface.co/c
 
 - [All examples](https://huggingface.co/docs/sagemaker/main/en/examples/introduction)
 
-## Blogs
+## Hugging Face Blogs
 
-- [AWS: Embracing natural language processing with Hugging Face](https://aws.amazon.com/de/blogs/opensource/embracing-natural-language-processing-with-hugging-face/)
 - [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/)
-- [Distributed Training: Train BART/T5 for Summarization using 🤗 Transformers and Amazon SageMaker](https://huggingface.co/blog/sagemaker-distributed-training-seq2seq)
+- [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)
-- [SageMaker's Distributed Data Parallel Library](https://docs.aws.amazon.com/sagemaker/latest/dg/data-parallel.html)
-- [SageMaker's Distributed Model Parallel Library](https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel.html)
+- [LLM Hosting Container](https://github.com/awslabs/llm-hosting-container)
+
 
 ## Workshops
 
-This part is under construction! Bear with us.
+- [Enterprise-Scale NLP with Hugging Face & Amazon SageMaker](https://github.com/philschmid/huggingface-sagemaker-workshop-series/tree/main)