Phi-3-Vision-128K-Instruct is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data both on text and vision. The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures.
Phi 3.5 Vision 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.
Generate a model response using the image endpoint of phi-3-vision-128k-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?"
}
]
}'On-demand deployments allow you to use Phi 3.5 Vision 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.
