TabPFN API Guide

Authentication

Interactive Login

The first time you use TabPFN, you'll be guided through an interactive login process:

from tabpfn_client import init
init()

Managing Access Tokens

You can save your token for use on other machines:

import tabpfn_client
# Get your token
token = tabpfn_client.get_access_token()

# Use token on another machine
tabpfn_client.set_access_token(token)

Rate Limits

Our API implements a fair usage system that resets daily at 00:00:00 UTC.

Usage Cost Calculation

The cost for each API request is calculated as:

api_cost = (num_train_rows + num_test_rows) * num_cols * n_estimators

Where n_estimators is by default 4 for classification tasks and 8 for regression tasks.

Monitoring Usage

Track your API usage through response headers:

Header	Description
X-RateLimit-Limit	Your total allowed usage
X-RateLimit-Remaining	Remaining usage
X-RateLimit-Reset	Reset timestamp (UTC)

Current Limitations

Important Data Guidelines

• Do NOT upload any Personally Identifiable Information (PII)
• Do NOT upload any sensitive or confidential data
• Do NOT upload any data you don't have permission to share
• Consider anonymizing or pseudonymizing your data
• Review your organization's data sharing policies

Size Limitations

1. Maximum total cells per request must be below 100,000:

   (num_train_rows + num_test_rows) * num_cols < 100,000
   

2. For regression with full output turned on (return_full_output=True), the number of test samples must be below 500.

These limits will be relaxed in future releases.

Managing User Data

You can access and manage your personal information:

from tabpfn_client import UserDataClient
print(UserDataClient.get_data_summary())

Error Handling

The API uses standard HTTP status codes:

Code	Meaning
200	Success
400	Invalid request
429	Rate limit exceeded

Example response, when limit reached:

{
    "error": "API_LIMIT_REACHED",
    "message": "Usage limit exceeded",
    "next_available_at": "2024-01-07 00:00:00"
}