I’m revamping one of our projects where we compare certain images found online with the baseline image the user provided. We launched this a while back when LLM’s where not yet that available and used a third party Nyckel software with a function we trained on some datasets. Now that the whole dynamic has shifted we’re looking for a better solution. I’ve been playing around with CLIP and Claude Vision, but I wonder if there’s a more sustainable way of using the LLM to train our system similar to what we had on Nyckel? Like using Open Router models to train the algo or what not? I’m exploring this cause we use ‘raw data’ for comparisson in a sense that the images are often bad quality or made “guerilla-style”, so CLIP/Claude vision often misjudge the scoring based on their rules or rather the lack off. Thnx for your help. submitted by /u/HeinsZhammer
Originally posted by u/HeinsZhammer on r/ClaudeCode