Example POC to run the Dolly V2 12B model in 8bit mode

After seeing a cool demo of a hack on Twitter, I built a cross platform version of it that works well and uses streaming. From anywhere on Mac and Linux, trigger Ollama and optionally feed it your clipboard. I built it yesterday and it's already very useful to me. I'm pretty excited about it and wanted to share!

Hey HN, I built a website where you can train Llama 3.1 8b & 70b (4bit) on your data. I use unsloth in the backend and the training is done on H100s which I rent programmatically from Runpod. I'd love some feedback. If you would be interested in using it feel free to book a chat with me: cal.com/hamada/tunellama-intro Happy to give you free credits :) P.S. I'm also looking for a co-founder as I have big plans for this.

Hi there, looking for feedback on my new project "Featherless.AI" The idea is to allow users to run all the models on hugging face instantly. Via the OpenAI API compatible endpoint. Why? Because its a real chore to download models and spin up GPUs, especially if you want to test multiple models. Not to mention GPUs cost multiple dollars an hour to rent. And if we want more people to use open source AI, we got to make it easier for them to try and play with all of them. So what if instead of spinning up dedicated GPUs per model (which is what every provider is doing) We can startup a LLM…

Another Sunday afternoon project: add some pizzaz to your boring bare metal or virtual machine consoles! Written as a single Go binary; no dependencies. https://github.com/Fusion/modernfbv As usual, feedback please!

Hey guys, I made a VS Code extension, within which you can use the Mixtral 8x7B AI model for free. Mixtral 8x7B is a new AI model from the Mistral family, which outperforms GPT-3 in many benchmarks, a fact that I have personally confirmed in daily coding tasks, where Mistral 8x7B was the clear winner. You can use all the AI features, such as AI Lens with custom instructions and similar. I'm pretty sure some of features will be useful to you. I'd appreciate both, positive and negative feedback!

I made this after seeing someone posit the idea online yesterday over lunch then spent some time refining it. So far it's pretty impressive IMO! Right now I am running Qwen3-30B-A3B on my 24gb unified memory m4 MacBook Pro at 50 tok/sec and this should definitely not be working for such a large model on my middling hardware. Things are detailed in the README to get up and running and DESIGN.md has details on all the choices and such made along the way.