#jupyter_notebook #ai #finetuning #langchain #llama #llama2 #llm #machine_learning #python #pytorch #vllm

The `llama-recipes` repository helps you get started with Meta's Llama models, including Llama 3.2 Text and Vision. It provides example scripts and notebooks for various use cases, such as fine-tuning the models and building applications. You can use these models locally, in the cloud, or on-premises. The repository includes guides for installing the necessary tools, converting models to Hugging Face format, and using features like multimodal inference and responsible AI practices. This makes it easier for you to quickly set up and use the Llama models for your projects, saving time and effort.

https://github.com/meta-llama/llama-recipes

#shell #ai #containers #inference_server #llamacpp #llm #podman #vllm

RamaLama is a tool that makes working with AI models easy by using containers. It checks your system for GPU support and uses CPU if no GPU is found. RamaLama uses container engines like Podman or Docker to run AI models, so you don't need to configure your system. You can pull and run AI models from various registries with simple commands, and it supports multiple types of hardware including CPUs and GPUs. This makes it convenient for users as they don't have to set up complex environments, and they can interact with different models easily.

https://github.com/containers/ramalama