Login & Sign Up

Home Pricing Help & Support Menu
intbanner-bg

The 72B variant of the latest iteration of Qwen-VL model from Alibaba, representing nearly a year of innovation.

Serverless API

Qwen2 VL 72B Instruct is available via Cyfuture AI' serverless API, where you pay per token. There are several ways to call the Cyfuture AI API, including Cyfuture AI' Python client, the REST API, or OpenAI's Python client.

See below for easy generation of calls and a description of the raw REST API for making API requests. See the Querying text models docs for details.

API Examples

Generate a model response using the image endpoint of qwen2-vl-72b-instruct. API reference

import requests
 import json
 
 url = "https://api.cyfuture.ai/aiapi/inferencing/response"
 payload = {
   "model": "Model Name",
   "max_tokens": 16384,
   "top_p": 1,
   "top_k": 40,
   "presence_penalty": 0,
   "frequency_penalty": 0,
   "temperature": 0.6,
   "messages": [
     {
       "role": "user",
       "content": "Hello, how are you?"
     }
   ]
 }
 headers = {
   "Accept": "application/json",
   "Content-Type": "application/json",
   "Authorization": "Bearer <API_KEY>"
 }
 requests.request("POST", url, headers=headers, data=json.dumps(payload))
await fetch("https://api.cyfuture.ai/aiapi/inferencing/response", {
   method: "POST",
   headers: {
     "Accept": "application/json",
     "Content-Type": "application/json",
     "Authorization": "Bearer <API_KEY>"
   },
   body: JSON.stringify({
     model: ""Model Name"",
     max_tokens: 16384,
     top_p: 1,
     top_k: 40,
     presence_penalty: 0,
     frequency_penalty: 0,
     temperature: 0.6,
     messages: [
         {
             role: "user",
             content: "Hello, how are you?"
         }
     ]
   })
 });
URI uri = URI.create("https://api.cyfuture.ai/aiapi/inferencing/response");
 HttpClient client = HttpClient.newHttpClient();
 HttpRequest request = HttpRequest.newBuilder()
   .uri(uri)
   .header("Accept", "application/json")
   .header("Content-Type", "application/json")
   .header("Authorization", "Bearer <API_KEY>")
   .POST(HttpRequest.BodyPublishers.ofString("""{
     "model": ""Model Name"",
     "max_tokens": 16384,
     "top_p": 1,
     "top_k": 40,
     "presence_penalty": 0,
     "frequency_penalty": 0,
     "temperature": 0.6,
     "messages": [
         {
             "role": "user",
             "content": "Hello, how are you?"
         }
     ]
   }"""))
   .build();
 HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
   
package main
 
 import (
   "bytes"
   "net/http"
   "fmt"
 )
 
 apiUrl := "https://api.cyfuture.ai/aiapi/inferencing/response"
 var jsonData = []byte(`{
  "model": "Model Name",
   "max_tokens": 16384,
   "top_p": 1,
   "top_k": 40,
   "presence_penalty": 0,
   "frequency_penalty": 0,
   "temperature": 0.6,
   "messages": [
     {
       "role": "user",
       "content": "Hello, how are you?"
     }
   ]
 }`)
 
 req, err := http.NewRequest(POST, apiUrl, bytes.NewBuffer(jsonData))
 req.Header.Set("Accept", "application/json")
 req.Header.Set("Content-Type", "application/json")
 req.Header.Set("Authorization", "Bearer <API_KEY>")
 
 client := &http.Client{}
 resp, err := client.Do(req)
 if err != nil {
   panic(err)
 }
 defer resp.Body.Close()
 
 fmt.Println("response Status:", resp.Status)
curl --request POST \
   --url https://api.cyfuture.ai/aiapi/inferencing/response \
   -H 'Accept: application/json' \
   -H 'Content-Type: application/json' \
   -H 'Authorization: Bearer <API_KEY>' \
   --data '{
    "model": "Model Name",
     "max_tokens": 16384,
     "top_p": 1,
     "top_k": 40,
     "presence_penalty": 0,
     "frequency_penalty": 0,
     "temperature": 0.6,
     "messages": [
         {
             "role": "user",
             "content": "Hello, how are you?"
         }
     ]
   }'

Fine-tuning

On-demand deployments allow you to use Qwen2 VL 72B Instruct on dedicated GPUs with Cyfuture AI' high-performance serving stack with high reliability and no rate limits

See the On-demand deployments guide for details.

Deploy this Base model
Open in model playground
Deploy this model

Model Details

Created by
[email protected]
Created
12/30/2024
Visibility
Public
Kind
Base model
Model size
14B parameters