#python #minicpm #minicpm_v #multi_modal

**MiniCPM-o 2.6** is a powerful multimodal model that can process images, videos, text, and audio, and provide high-quality outputs. Here are the key benefits It achieves comparable performance to GPT-4o-202405 in vision, speech, and multimodal live streaming, making it highly versatile.
- **Real-Time Speech Conversation** Outperforms proprietary models like GPT-4V and Claude 3.5 Sonnet in single image, multi-image, and video understanding.
- **Efficient Deployment** Can be used in various ways, including CPU inference with llama.cpp, quantized models, fine-tuning, and local WebUI demos.

This model enhances user experience by providing accurate and efficient multimodal interactions, making it a valuable tool for various applications.

https://github.com/OpenBMB/MiniCPM-o

#jupyter_notebook #chatglm #chatglm3 #gemma_2b_it #glm_4 #internlm2 #llama3 #llm #lora #minicpm #q_wen #qwen #qwen1_5 #qwen2

This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5].

https://github.com/datawhalechina/self-llm