#go #gemma #gemma2 #go #golang #llama #llama2 #llama3 #llava #llm #llms #mistral #ollama #phi3

Ollama is a tool that lets you use large language models on your own computer. You can download and install it for macOS, Windows, or Linux. It supports various models like Llama 3.2, Phi 3, and others, which you can run locally using simple commands. For example, to run the Llama 3.2 model, you just need to type `ollama run llama3.2`.

The benefit to you is that you can use powerful language models without relying on cloud services, ensuring your data stays private and secure. You can also customize the models with specific prompts and settings to fit your needs. Additionally, there are many community integrations and libraries available to extend its functionality in various applications.

https://github.com/ollama/ollama

#python #deepseek #deepseek_r1 #fine_tuning #finetuning #gemma #gemma2 #llama #llama3 #llm #llms #lora #mistral #phi3 #qlora #unsloth

Using Unsloth.ai, you can finetune AI models like Llama, Mistral, and others up to 2x faster and with 70% less memory. The process is beginner-friendly; you just need to add your dataset, click "Run All" in the provided notebooks, and you'll get a faster, finetuned model that can be exported or uploaded to platforms like Hugging Face. This saves time and resources, making it easier to work with large AI models without needing powerful hardware. Additionally, Unsloth supports various features like 4-bit quantization, long context windows, and integration with tools from Hugging Face, making it a powerful tool for AI model development.

https://github.com/unslothai/unsloth

#go #gemma3 #go #gpt_oss #granite4 #llama #llama3 #llm #on_device_ai #phi3 #qwen3 #qwen3vl #sdk #stable_diffusion #vlm

NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience.

https://github.com/NexaAI/nexa-sdk