Fine-Tuning a FM
Learn about the different methods to fine-tune a foundational model
We'll cover the following...
Fine-tuning refers to the process of taking a pretrained foundational model and adjusting its weights and parameters to perform better on a specific task. Instead of the resource-intensive process of training a model from scratch, fine-tuning allows us to leverage the knowledge embedded in a large, pretrained model and adapt it to our own data and requirements.
Amazon Bedrock provides us with access to foundational models from various providers. However, only the following FMs support fine-tuning:
Amazon Titan Text G1: Express, G1 Lite, and Premier
Amazon Titan Multimodal Embeddings G1
Amazon Titan Image Generator G1: V1 and V2
Anthropic Claude 3: Haiku
Cohere: Command and Light
Meta Llama 2: 13B and 70B
Meta Llama 3.1: 8B Instruct and 70B Instruct ...