The flagship, 70 billion parameter language model from Meta, fine tuned for chat completions. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety.
Sample code and API for Llama v2 70B Chat
OpenRouter normalizes requests and responses across providers for you.
To get started, you can use Llama v2 70B Chat via API like this:
fetch("https://openrouter.ai/api/v1/chat/completions",{ method:"POST", headers:{"Authorization":`Bearer ${OPENROUTER_API_KEY}`,"HTTP-Referer":`${YOUR_SITE_URL}`,// Optional, for including your app on openrouter.ai rankings."X-Title":`${YOUR_SITE_NAME}`,// Optional. Shows in rankings on openrouter.ai."Content-Type":"application/json"}, body:JSON.stringify({"model":"meta-llama/llama-2-70b-chat","messages":[{"role":"user","content":"What is the meaning of life?"},],})});
You can also use OpenRouter with OpenAI's client API:
import OpenAI from"openai"const openai =newOpenAI({ baseURL:"https://openrouter.ai/api/v1", apiKey: $OPENROUTER_API_KEY, defaultHeaders:{"HTTP-Referer": $YOUR_SITE_URL,// Optional, for including your app on openrouter.ai rankings."X-Title": $YOUR_SITE_NAME,// Optional. Shows in rankings on openrouter.ai.}})asyncfunctionmain(){const completion =await openai.chat.completions.create({ model:"meta-llama/llama-2-70b-chat", messages:[{ role:"user", content:"Say this is a test"}],})console.log(completion.choices[0].message)}main()
See the Request docs for all possible parameters, and Parameters for recommended values.