ai ai

AI model ai

the aim is to incorporate it into aibot and aios.

name	full	code	repo
ai	ai ai	aiai	https://git.syui.ai/ai/ai
os	ai os	aios	https://git.syui.ai/ai/os
bot	ai bot	aibot	https://git.syui.ai/ai/bot
at	ai	ai.syu.is	https://git.syui.ai/ai/at

model

1. gemma3:12b
2. deepseek-r1:12b

{
    "model": [ "gemma3", "deepseek-r1" ],
    "tag": [ "ollama", "LoRA", "unsloth", "open-webui", "n8n" ]
}

$ brew install ollama
$ brew service restart ollama
$ ollama pull gemma3:12b
$ ollama run gemma3:12b "hello"

n8n

# https://github.com/n8n-io/n8n/
$ docker volume create n8n_data
$ docker run -it --rm --name n8n -p 5678:5678 -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8n

webui

$ winget install ollama.ollama
$ ollama server
$ ollama run llama3.2:1b

$ winget install --id Python.Python.3.11 -e
$ python --version
$ python -m venv webui
$ cd webui
$ .\Scripts\activate
$ pip install open-webui
$ open-webui serve

http://localhost:8080

LoRA

finetuning

# https://ai.google.dev/gemma/docs/core/lora_tuning
$ conda create -n finetuning python=3.11
$ conda activate finetuning
$ pip install mlx-lm #apple silicon
$ ollama run llama3.2:1b
$ echo "{ \"model\": \"https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct\", \"data\": \"https://github.com/ml-explore/mlx-examples/tree/main/lora/data\" }"|jq .
$ model=meta-llama/Llama-3.2-1B-Instruct
$ data=ml-explore/mlx-examples/lora/data
$ mlx_lm.lora --train --model $model --data $data --batch-size 3

$ ls adapters
$ vim Modelfile
FROM llama3.2:1b
ADAPTER ./adapters

$ ollama create ai -f ./Modelfile

unsloth

$ pip install unsloth

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="Qwen2.5-1.5B",
    grpo=True
)