One ting is that while getting the value of running pretrained model weights like OPT-175B, there are also a potential downsides to using pre-trained models, such as the need to fine-tune the model to your specific task, potential compatibility issues with your existing infrastructure (integration ) , and the possibility that the pre-trained model may not perform as well as a model trained specifically on your data. Ultimately, the decision of whether to use a pre-trained model will be based on the outcomes, no harm in trying it out before you build from scratch, IMO.