georgedavila/tableqa-tapas-large | Run with an API on Replicate

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=georgedavila/tableqa-tapas-large

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run georgedavila/tableqa-tapas-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "georgedavila/tableqa-tapas-large:d803a5ffe8a515d47966beedb2076a747cac5e94e4a8e47aaf44ad88817420b9",
  {
    input: {
      query: "What age was Charles Alexander Fortune?",
      numRows: 35,
      userFileType: "csv"
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run georgedavila/tableqa-tapas-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "georgedavila/tableqa-tapas-large:d803a5ffe8a515d47966beedb2076a747cac5e94e4a8e47aaf44ad88817420b9",
    input={
        "query": "What age was Charles Alexander Fortune?",
        "numRows": 35,
        "userFileType": "csv"
    }
)

print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run georgedavila/tableqa-tapas-large using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "georgedavila/tableqa-tapas-large:d803a5ffe8a515d47966beedb2076a747cac5e94e4a8e47aaf44ad88817420b9",
    "input": {
      "query": "What age was Charles Alexander Fortune?",
      "numRows": 35,
      "userFileType": "csv"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/georgedavila/tableqa-tapas-large@sha256:d803a5ffe8a515d47966beedb2076a747cac5e94e4a8e47aaf44ad88817420b9 \
  -i 'query="What age was Charles Alexander Fortune?"' \
  -i 'numRows=35' \
  -i 'userFileType="csv"'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/georgedavila/tableqa-tapas-large@sha256:d803a5ffe8a515d47966beedb2076a747cac5e94e4a8e47aaf44ad88817420b9
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "query": "What age was Charles Alexander Fortune?",
      "numRows": 35,
      "userFileType": "csv"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia T4 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.