mi12-root

3 ms·

1. 1.▲
   by mi12-root 1y ago

   Thanks for sharing the details—that makes a lot of sense. Fine-tuning and exporting models on-device can be tedious nowadays. We’re planning to look into supporting popular on-device LLM models more directly, so deployment feels much easier
2. 2.▲
   by mi12-root 1y ago

   I tested the system LLM with a long article using two prompts: one asking for a summary in at most 20 words, and another asking for a one-sentence summary. In both cases, the model followed the instructions correctly. Regarding your second
3. 3.▲
   by mi12-root 1y ago

   While we did use AI coding tools, we put significant thought into the design of SwiftAI and would greatly value feedback on it (see system design doc above). All AI-generated code was carefully reviewed and often, rewritten (no yolo)
4. 4.▲
   by mi12-root 1y ago

   That’s a good suggestion, and it indeed sounds like something we’d want to support. Could you help us better understand your use case? For example, where do you usually get the models (e.g., Hugging Face)? Do you fine-tune them? Do you most
5. 5.▲
   by mi12-root 1y ago

   Thanks for the feedback! When you say “custom,” do you mean additional integrations with LLM providers, or more documentation on how to build your own custom integration? If you mean the former, we’re currently focused on stabilizing the AP
6. 6.▲
   by mi12-root 1y ago

   We’ve begun internally evaluating the model and will share our findings more in details later. So far, we’ve found that it performs well on tasks such as summarization, writing, and data extraction, and shows particular strength in areas li
7. 7.▲
   Show HN: SwiftAI – open-source library to easily build LLM features on iOS/macOS(github.com)

   74 points by mi12-root 1y ago|24 comments