Hey Simon, I'm happy to oblige here. What would be the most exciting, definitive demonstration?
Do you have a dataset or task in mind?
Do you have a dataset or task in mind?
1. A fine-tuned model for structured data extraction. Get something that's REALLY good at outputting in a specific JSON format, then show it running against a wide range of weird inputs.
2. A fine-tuned vision LLM that gains a new ability that the underlying model did not have, such as identifying different breeds of common California garden birds
3. Text to SQL. Text to SQL is always a great demo for this stuff, a fine-tuned model that's demonstrably "better" at text to SQL for a specific complex database schema would be a really great example.
https://www.llama.com/static-resource/llama-case-study-shopi...
I'd be happy to create you a base agent, and a fine-tuned agent, and OSS the traces for you to look at differently.
And if it's really compelling, visualize them in a hosted frontend :-)
1) the training configuration and code 2) the data used to fine tune 3) a set of input/output comparisons comparing the tuned bot to the original bot that show it's learned something interesting
For something really compelling it would host the created models on a repo that I could download and use. The gold standard would be to host them and provide a browser interface, but this could be expensive for gpu costs.
This blog post currently doesn't exist, or if it does I haven't been able to find it in the sea of medium articles detailing an outdated hugging face api