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Train LLMs using QLoRA on Amazon SageMaker

philschmid.de·148w

Deploy LLMs with Hugging Face Inference Endpoints

philschmid.de·149w

Optimize and Deploy BERT on AWS inferentia2

philschmid.de·150w

Securely deploy LLMs inside VPCs with Hugging Face and Amazon SageMaker

philschmid.de·151w

Deploy Falcon 7B and 40B on Amazon SageMaker

philschmid.de·153w

Fine-tune BERT for Text Classification on AWS Trainium

philschmid.de·153w

Introducing the Hugging Face LLM Inference Container for Amazon SageMaker

philschmid.de·154w

Generative AI for Document Understanding with Hugging Face and Amazon SageMaker

philschmid.de·155w

How to scale LLM workloads to 20B+ with Amazon SageMaker using Hugging Face and PyTorch FSDP

philschmid.de·158w

Setting up AWS Trainium for Hugging Face Transformers

philschmid.de·159w

Train and Deploy BLOOM with Amazon SageMaker and PEFT

philschmid.de·161w

Introducing IGEL an instruction-tuned German large Language Model

philschmid.de·162w

Efficient Large Language Model training with LoRA and Hugging Face

philschmid.de·164w

Deploy FLAN-UL2 20B on Amazon SageMaker

philschmid.de·164w

Getting started with Pytorch 2.0 and Hugging Face Transformers

philschmid.de·165w

Controlled text-to-image generation with ControlNet on Inference Endpoints

philschmid.de·166w

Combine Amazon SageMaker and DeepSpeed to fine-tune FLAN-T5 XXL

philschmid.de·168w

Fine-tune FLAN-T5 XL/XXL using DeepSpeed and Hugging Face Transformers

philschmid.de·169w

Deploy FLAN-T5 XXL on Amazon SageMaker

philschmid.de·170w

Hugging Face Transformers Examples

philschmid.de·172w

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