Mistral AI logoPixtral 12B

A multimodal (text + image) LLM from Mistral

Deploy Pixtral 12B behind an API endpoint in seconds.

Deploy model

Example usage

Pixtral 12B has optional streaming, temperature, and maximum token settings.

Input
1import requests
2import os
3
4# Replace the empty string with your model id below
5model_id = ""
6baseten_api_key = os.environ["BASETEN_API_KEY"]
7
8messages = [
9   {
10      "role":"system",
11      "content":"You are a pirate chatbot who always responds in pirate speak!"
12   },
13   {
14      "role":"user",
15      "content":[
16         {
17            "type":"text",
18            "text":"What is this?"
19         },
20         {
21            "type":"image_url",
22            "image_url":{
23               "url":"https://easydrawingguides.com/wp-content/uploads/2018/03/how-to-draw-a-pirate-ship-featured-image-1200.png"
24            }
25         }
26      ]
27   }
28]
29data = {
30    "messages": messages,
31    "stream": True,
32    "temperature": 0.5,
33    "max_tokens": 512
34}
35
36# Call model endpoint
37res = requests.post(
38    f"https://model-{model_id}.api.baseten.co/production/predict",
39    headers={"Authorization": f"Api-Key {baseten_api_key}"},
40    json=data,
41    stream=True
42)
43
44# Print the generated tokens as they get streamed
45for content in res.iter_content():
46    print(content.decode("utf-8"), end="", flush=True)
JSON output
1[
2    "Arr",
3    "matey,",
4    "ye",
5    "be",
6    "lookin'",
7    "at",
8    "..."
9]

Deploy any model in just a few commands

Avoid getting tangled in complex deployment processes. Deploy best-in-class open-source models and take advantage of optimized serving for your own models.

$

truss init -- example stable-diffusion-2-1-base ./my-sd-truss

$

cd ./my-sd-truss

$

export BASETEN_API_KEY=MdNmOCXc.YBtEZD0WFOYKso2A6NEQkRqTe

$

truss push

INFO

Serializing Stable Diffusion 2.1 truss.

INFO

Making contact with Baseten 👋 👽

INFO

🚀 Uploading model to Baseten 🚀

Upload progress: 0% | | 0.00G/2.39G