A blazing fast vision-language model, FireLLaVA quickly understands both text and images. It achieves impressive chat skills in tests, and was designed to mimic multimodal GPT-4.
The first commercially permissive open source LLaVA model, trained entirely on open source LLM generated instruction following data.
Sample code and API for FireLLaVA 13B
OpenRouter normalizes requests and responses across providers for you.
To get started, you can use FireLLaVA 13B 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":"fireworks/firellava-13b","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:"fireworks/firellava-13b", 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.