Pure RL With DeepSeek
So apparently pure reinforcement learning is the move. The new DeepSeek models out of China throw modern LLM training techniques out in favor of just purely using RL over more time and over more data to produce better models than the more bespoke methods.
Open Source Stacks Rock!
I've experienced it once before with ComfyUI, but it seems like with AI the open source community has really been putting in the work so those like me looking to start some passion projects can quicken their development cycles.
OpenWebUI is a great frontend UI for interacting with models. Some of their docker containerscome bundled with Ollama, which means the setup is literally as simple as building a super standard docker container with it.
DeepSeek
This is the new LLM model out of China that's been said to have pretty good code gen abilities, and the main reason I started looking at setting up this stack for myself. I've done previous attempts at self-hosting coding assistants, but found that the juice wasn'tworth the squeeze, as they say.
For this experiment I was looking at the 1.5b and 8b models for deepseek-r1, though the coding assistant model deepseek-coder is also available.
My Experience
Man, it was pretty good. I've got a smaller GPU on PWS so I was limited to running the 8b model, but responses were good. I noticedthe best response times on the 1.5b model, and for some easier tasks the correctness between the two was hard to discern.
I particularly liked the features of OpenWebUI to allow for web search, which from initial testing seemed to find good results to buildcontext of the response with.
Some responses with web search are a little on the nose with the smaller models, for example a search about me gives results that are pulled verbatim from my github profile and websites.
I'm still actively using ChatGPT, Claude, and others for coding work, but as local LLMs improve you can bet I'll be keeping up to date with this stack.
Resources
Thank you to DWS for collaboration.