Interactive fine-tuning of Foundation Models with Amazon SageMaker Training using @remote decorator

Important: The scope of these notebook examples is to showcase interactive experience with SageMaker AI capabilities and @remote decorator, for Small/Large Language Models fine-tuning by using different distribution techniques, such as FSDP, and DDP.

In this example we will go through the steps required for interactively fine-tuning foundation models on Amazon SageMaker AI by using @remote decorator for executing Training jobs.

You can run this repository from Amazon SageMaker Studio or from your local IDE.

For additional information, take a look at the AWS Blog Fine-tune Falcon 7B and other LLMs on Amazon SageMaker with @remote decorator

Prerequistes

The notebooks are currently using the latest PyTorch Training Container available for the region us-east-1. If you are running the notebooks in a different region, make sure to update the ImageUri in the file config.yaml.

Make sure the Python version in your local environment matches the one in the used container

Python version used in the training container: Python 3.11

If you want to operate in a different AWS region

1. Navigate [Available Deep Learning Containers Images](Available Deep Learning Containers Images)
2. Select the right Hugging Face TGI container for model training based on your selected region
3. Update ImageUri in the file config.yaml

Notebooks

1. [Supervised - QLoRA] Falcon-7B
2. [Supervised - QLoRA, FSDP] Llama-13B
3. [Self-supervised - QLoRA, FSDP] Llama-13B
4. [Self-supervised - QLoRA] Mistral-7B
5. [Supervised - QLoRA, FSDP] Mixtral-8x7B
6. [Supervised - QLoRA, DDP] Code-Llama 13B
7. [Supervised - QLORA, DDP] Llama-3 8B
8. [Supervised - QLoRA, DDP] Llama-3.1 8B
9. [Supervised - QLoRA, DDP] Arcee AI Llama-3.1 Supernova Lite
10. [Supervised - QLoRA] Llama-3.2 1B
11. [Supervised - QLoRA] Llama-3.2 3B
12. [Supervised - QLoRA, FSDP] Codestral-22B
13. [Supervised - LoRA] TinyLlama 1.1B
14. [Supervised - LoRA] Arcee Lite 1.5B
15. [Supervised - LoRA] SmolLM2-1.7B-Instruct
16. [Supervised - QLORA, FSDP] Qwen 2.5 7B
17. [Supervised - QLORA] Falcon3 3B
18. [Supervised - QLORA, FSDP] Falcon3 7B
19. [Supervised - QLORA, FSDP] Llama-3.1 70B
20. [Self-supervised - DoRA, FSDP] Mistral-7B v0.3
21. [Supervised - QLORA, FSDP] Llama-3.3 70B
22. [Supervised - QLORA, FSDP] OpenCoder-8B-Instruct
23. [Supervised - QLORA, FSDP] DeepSeek-R1-Distill-Qwen-32B
24. [Supervised - QLORA, FSDP] DeepSeek-R1-Distill-Llama-70B
25. [Supervised - QLORA, FSDP] DeepSeek-R1-Distill-Llama-8B
26. [Supervised - QLORA, DDP] DeepSeek-R1-Distill-Qwen-1.5B
27. [Supervised - QLORA, FSDP] DeepSeek-R1-Distill-Qwen-7B
28. [Supervised - QLORA, FSDP] Mistral-Small-24B-Instruct-2501