kth8
kth8
just use the split method? ``` import wikipediaapi wiki_wiki = wikipediaapi.Wikipedia(user_agent='john ([email protected])',language='en') url = "https://en.wikipedia.org/wiki/GitHub" page = wiki_wiki.page(url.split("/")[-1]) if page.exists(): print(page.title) print(page.summary) ```
I made a Homebrew tap for this `brew install kth8/tap/shellgpt` https://github.com/kth8/homebrew-tap
The repo with Quantization-Aware Training is `lmstudio-community/gemma-3-12B-it-qat-GGUF`
I think integrating openedai-speech would be a good improvement similar to how Open WebUI is able to do.
The README advertise their paid service for `ultra-low latency of sub 200ms—ideal for production use in agents, applications, or interactive media.`
I'm surprised the official `ollama/ollama` is still based on Ubuntu 20.04 which will reach end of life this month.
The current models available are not instruct models so they won't give you answer like you are used to but instead act more like autocompletes.
I saw this project from Reddit and it looks pretty cools. I tested this using Open WebUI and it worked well although the speed is noticeably slower compared to using...
I remembered this project [tgpt](https://github.com/aandrew-me/tgpt) is written in Go and also connects to DuckDuckGo's AI Chat so perhaps you can take a look at their implementation and use it as...
no, you'd want to use these model for STT: https://huggingface.co/spaces/hf-audio/open_asr_leaderboard