Alpaca 7B

Alpaca 7B is a language model developed by Stanford University, derived from Meta's LLaMA 7B, designed for instruction-following tasks. It excels in producing coherent, context-sensitive responses and is comparable to OpenAI's text-davinci-003, despite its smaller size and lower training costs. With a transformer-based architecture of 7 billion parameters, it efficiently balances performance and resource needs, suitable for devices like laptops. Trained on 52,000 instruction-based demonstrations, it offers high-quality interaction while facing challenges like hallucination and stereotyping, indicating a need for careful real-world application.

Alpaca 7B is a model in the Alpaca family. The structured metadata tracks a 2k-token context window and structured outputs. This page tracks provider routes through Together AI, with the cheapest tracked route listed at $0.2 input and $0.2 output per 1M tokens. No headline benchmark score is tracked for Alpaca 7B yet.