LLaMA

LLaMA is a family of large language models developed by Meta, designed as a general-purpose foundation for research and real-world NLP applications. It is intended for researchers, startups, and enterprises that want to experiment with or deploy advanced language models under a flexible license.

LLaMA is released under a custom license that allows use for research and, for many users, commercial applications, but it is not a pure permissive open-source license like Apache 2.0. Users must review and comply with Meta's official license terms before downloading or deploying the model.

Hardware requirements depend on the chosen model size. Smaller variants can run on a single modern GPU or high-memory CPU server, while larger models may require multiple GPUs and more memory. Many users also run LLaMA via optimized inference frameworks or managed cloud services to simplify deployment.

Yes. LLaMA is designed to be fine-tuned on custom datasets so you can adapt it to specific domains, tasks, or brands. Techniques such as full fine-tuning, LoRA, or other parameter-efficient methods can be used depending on your hardware and requirements.

LLaMA itself is a base model and may require additional safety layers, alignment, and content filtering for production use. You should implement safeguards such as prompt filtering, output moderation, and domain-specific policies when integrating LLaMA into user-facing applications.