List Available images

Next, you’ll choose an image template that provides the required environment for your GPU instance, such as "PyTorch" or "TensorFlow". Selecting an appropriate image template ensures the instance is configured with the software and dependencies needed for your workload.

If none of the platform-provided image templates meet your requirements, you can create a custom image template. You can also implement these in the custom template:

• Map a service on a specific IP to the internet.

• Run VSCode or Jupyter in a web-based interface.

Please refer to the "Full API Reference"-"Rent GPU"-"POST /v1/rentgpu/images" for details on how to create and manage custom image templates.

Example Request:

Replace {{API_TOKEN}} with your actual token.

Curl

curl --location 'https://api.netmind.ai/v1/rentgpu/images?limit=10&marker=12' \
--header 'Authorization: Bearer {{API_TOKEN}}'

Python

import requests

url = "https://api.netmind.ai/v1/rentgpu/images?limit=10&marker=12"

payload = {}
headers = {
  'Authorization': 'Bearer {{API_TOKEN}}'
}

response = requests.request("GET", url, headers=headers, data=payload)

print(response.text)

Example Response:

[
    {
        "name": "default",
        "description": "pytoch/pytorch:latest",
        "image_name": "pytoch/pytorch",
        "image_tag": "latest",
        "image_label": "default",
        "docker_username": null,
        "docker_passwd": null,
        "docker_registry": null,
        "public_port": null,
        "onstart": null,
        "options": null,
        "image_type": 0,
        "id": 0
    },
    ...
]