I did something related for my ChillTranslator project for translating spicy HN comments to calm variations which has a GGUF model that runs easily and quickly but it's early days. I did it with a much smaller set of data, using LLM's to make calm variations and an algo to pick the closest least spicy one to make the synthetic training data then used Phi 2. I used Detoxify then OpenAI's sentiment analysis is free, I use that to verify Detoxify has correctly identified spicy comments then generate a calm pair. I do worry that HN could implode / degrade if there is not able to be a good balance for the comments and posts that people come here for. Maybe I can use your sentiment data to mine faster and generate more pairs. I've only done an initial end-to-end test so far (which works!). The model, so far is not as high quality as I'd like but I've not used Phi 3 on it yet and I've only used a very small fine-tune dataset so far. File is here though: https://huggingface.co/lukestanley/ChillTranslator I've had no feedback from anyone on it though I did have a 404 in my Show HN post!