LLMs contain built-in policies for protecting minors, animals etc. Monkey eating sausage should be against policy. But it can be fooled and finally model stops complaining and describe what we want to. Tried: to generate funny/controversial pictures. Actuall image generate takes place at Stable Diffusion and not at those conversational LLMs. However, once aksed to generate something dubious or funny they tend to reject such requests hiding befind their policies. Refusals from nexusraven and granite3-dense First I asked for Proboscis Monkey holding can of beer and eating sausage. LLM model called nexusraven refused with that request: nexusraven: I cannot fulfill
I want to create custom chatbot experience. I want to be based on Google’s Gemma AI Large Language Models. I find Gemma3, especially 27b version very capable while problem solving. It has been trained on such data that I find it interesting. I will use Open WebUI to create custom “model hat” and provide chatbot experience TLDR In order to create your own chatbot, only 3 steps are required: To create own chatbot experience I can use System Prompt feature which is core part of model itself. Running on Ollama, Gemma3:27b is actually a 4-bit quantized version of full 16-bit
slight utlization drop when dealing with multi GPU setup TLDR Power usage and GPU utilization varies between single GPU models and multi GPU models. Deal with it. My latest finding is that single GPU load in Ollama/Gemma or Automatic1111/StableDiffusion is higher than using multiple GPUs load with Ollama when model does not fit into one GPU’s memory. Take a look. GPU utilization of Stable Diffusion is at 100% with 90 – 100% fan speed and temperature over 80 degress C. Compare this to load spread across two GPUs. You can clearly see that GPU utilization is much lower, as well
With Ollama paired with Gemma3 model, Open WebUI with RAG and search capabilities and finally Automatic1111 running Stable Diffusion you can have quite complete set of AI features at home in a price of 2 consumer grade GPUs and some home electricity. With 500 iterations and image size of 512×256 it took around a minute to generate response. I find it funny to be able to generate images with AI techniques. Tried Stable Diffusion in the past, but now with help of Gemma and integratino with Automatic1111 on WebUI, it’s damn easy. Step by step Prerequisites You can find information