/Finetune-Llama2-7B-on-Financial-data-with-Sagemaker

Primary LanguageJupyter Notebook

Fine-tuning LLama2-7b on Financial Data using AWS SageMaker:

Project Description

  • Utilize Amazon Sagemaker and s3 bucket AWS tools to fine-tune the Meta Llama 2 7B foundation model.
  • This model has been trained for text-generation tasks. The goal is to adapt this model to your selected domain, enhancing its ability to understand and generate domain-specific text.

Steps:

  • Upload the Domain Data to s3 bucket
  • Create AWS SageMaker role and attach the required persmission specially the Fulls3bucketAcceess image image
  • Create Sakemaker notebook instance with the role created in the previous step image
  • Fine-tune the model on your chosen dataset using training notebook
  • Test and evaluate the model for its responses to domain knowledge and text-generation tasks using evaluation notebook
  • Deploy the fine-tuned model
  • Test the fine-tuned model on domain-specific knowledge and text generation tasks relevant to your dataset.