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✏️ I wrote and published my notes on using the Ollama service micro.webology.dev/2024/06/11…
Just finished and published a web interface for Ollama 
#ollamachat
🤖 played with Aider and it mostly working with Ollama + Llama 3.1 
#research
🤖 played around with adding extra context in some local Ollama models. Trying to test out some real-world tasks I'm tired of doing. #research
removed all ollama models except one 
#leifinlavida
🤖 Tried out Llama 3.3 and the latest Ollama client for what feels like flawless local tool calling. #research
🤖 more working with Ollama and Llama 3.1 and working on a story writer as a good enough demo. #research
implemented ollama local models 
#rabbitholes
🦙 added ollama and settings to my 
#dotfiles since it works so well
created several personal AI agents via ollama #leifinlavida
read up on llm embedding to start building something new with ollama
✏️ wrote about running Llama 3.1 locally through Ollama on my Mac Studio. micro.webology.dev/2024/07/24…
🤖 Updated some scripts to use Ollama's latest structured output with Llama 3.3 (latest) and fell back to Llama 3.2. I drop from >1 minute with 3.3 down to 2 to 7 seconds per request with 3.2. I can't see a difference in the results. For small projects 3.2 is the better path. #research
🤖 spent my evening writing a better console for some more advanced Ollama 3.1 projects. #research
🤖 played with Ollama's tool calling with Llama 3.2 to create a calendar management agent demo #research
prototype a simple autocomplete using local llama2 via Ollama 
#aiplay
🤖 Created an Ollama + Llama 3.2 version of my job parser to compare to ChatGPT. It's not bad at all, but not as good as GPT4. 
#jobs
🤖 spent some time getting Ollama and langchain to work together. I hooked up tooling/function calling and noticed that I was only getting a match on the first function call. Kind of neat but kid of a pain.