Using Llama 2 13B Chat on Cloudflare Workers AI
Implementation guide · Llama 2 · AI at Meta
Quick Start
- 1
- 2Use the Cloudflare Workers AI SDK or REST API to call
llama2-13b-chat— see the documentation for request format.
Code Examples
About Cloudflare Workers AI
Cloudflare Workers AI is a serverless GPU inference platform enabling developers to run machine learning models on Cloudflare's global edge network. It supports diverse AI tasks including text generation, image classification, automatic speech recognition, and real-time language translation. The platform provides pay-per-use pricing and access to a curated library of open-source models from Hugging Face, enabling rapid deployment without complex infrastructure management. Key features include low-latency edge computing, streaming responses for large language models, context length customization, and the AI Gateway for monitoring, caching, and cost optimization.
Cloudflare is a leading connectivity cloud company that provides a comprehensive suite of cloud-native products and developer tools to enhance web performance, security, and reliability. Their services include content delivery network (CDN), DDoS mitigation, DNS services, and zero trust security solutions. While Cloudflare doesn't primarily market itself as an AI platform, they have incorporated AI and machine learning technologies into various aspects of their services to improve performance and security, including threat detection capabilities, content delivery optimization, and intelligent routing decisions across their global network.
Pricing on Cloudflare Workers AI
Capabilities
About Llama 2 13B Chat
The Llama 2 13B Chat model is a 13 billion parameter generative text model developed by Meta, optimized for conversational applications. Released on July 18, 2023, it's part of the Llama 2 family and excels in dialogue scenarios. The model leverages supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to generate coherent and contextually relevant responses. Trained on 2 trillion tokens from diverse public sources, it outperforms many open-source chat models and matches popular closed-source models in helpfulness and safety. This model is ideal for AI engineers working on chatbots, virtual assistants, and customer service automation. For more details, visit the model's Hugging Face page [1].