Adding new LLMs, text classification and code generation models to the Workers AI catalog

What this post added

This post announces the addition of eight new models to the Workers AI catalog, including text generation models like Llama-2-13b-chat-awq, Zephyr-7b-beta-awq, Mistral-7b-instruct-v0.1-awq, OpenHermes-2.5-Mistral-7b-awq, Neural-chat-7b-v3-1-awq, and Llamaguard-7b-awq, as well as code generation models like Deepseek-coder-6.7b-base-awq and Deepseek-coder-6.7b-instruct-awq. It highlights the performance advantages of Deepseek-coder and OpenHermes-2.5-Mistral-7b due to their training data and fine-tuning. The post also introduces Activation-aware Weight Quantization (AWQ) as a technique for improving memory efficiency in LLMs. A new use case, prompt and response classification with LlamaGuard, is detailed with a code example demonstrating how to use it to detect unsafe content.