Not trolling, though I feel the same way about you with this post haha. To answer your question, this library doesn't provide something like a `chat` method an

Not trolling, though I feel the same way about you with this post haha. To answer your question, this library doesn't provide something like a `chat` method and doesn't provide anything like Stable Diffusion's `img2img` API either - that's not what it is - it's a library for predicting the next token (letter, word, pixel, etc.) based on data you train it on. The most typical use cases for this model are: Auto-completion, auto-correct, spell check, search, etc. However, if you watched the incredible video I shared in the original post you'd know that this completion concept can be applied to other interfaces: Chat, image generation, audio analysis/generation, etc. and in fact it is applied to LLMs like GPT. This library doesn't get into any chat-specific methods like `ask` (question & answer), it just completes token sequences. If your goal is to create a ChatGPT clone, you would have to add methods like `chat`, `ask`, etc. and provide code for ongoing conversations - probably using an NLP library to parse queries into cursors like I'm trying in another project, or use "MULTI-HEADED ATTENTION BLOCKS" (lmfao) if you fancy that. Or if you wanted to create a Stable Diffusion clone, you'd have to provide those image-related methods needed. As far as the meaning of "from scratch" - I mean compared to using Ollama etc. to run local models or using OpenAI - just trying to enable you to build whatever model suits your data and use case.