lucataco/apollo-7b – Run with an API on Replicate

lucataco / apollo-7b

Apollo 7B - An Exploration of Video Understanding in Large Multimodal Models

Cold

Public
2.5K runs
L40S
GitHub
Weights
Paper
License

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=lucataco/apollo-7b

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 lucataco/apollo-7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/apollo-7b:e282f76d0451b759128be3e8bccfe5ded8f521f4a7d705883e92f837e563f575",
  {
    input: {
      top_p: 0.7,
      video: "https://replicate.delivery/pbxt/M9kGHuJMeAKZs0eSbaEk6hCc7zqY4Tg94IxWwDpC5hRiuBPY/astro.mp4",
      prompt: "Describe this video in detail",
      temperature: 0.4,
      max_new_tokens: 256
    }
  }
);

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 lucataco/apollo-7b using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/apollo-7b:e282f76d0451b759128be3e8bccfe5ded8f521f4a7d705883e92f837e563f575",
    input={
        "top_p": 0.7,
        "video": "https://replicate.delivery/pbxt/M9kGHuJMeAKZs0eSbaEk6hCc7zqY4Tg94IxWwDpC5hRiuBPY/astro.mp4",
        "prompt": "Describe this video in detail",
        "temperature": 0.4,
        "max_new_tokens": 256
    }
)
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 lucataco/apollo-7b 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": "e282f76d0451b759128be3e8bccfe5ded8f521f4a7d705883e92f837e563f575",
    "input": {
      "top_p": 0.7,
      "video": "https://replicate.delivery/pbxt/M9kGHuJMeAKZs0eSbaEk6hCc7zqY4Tg94IxWwDpC5hRiuBPY/astro.mp4",
      "prompt": "Describe this video in detail",
      "temperature": 0.4,
      "max_new_tokens": 256
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

The video features an astronaut in a white spacesuit walking on the moon's surface. The background showcases a large, detailed moon against a starry sky. As the astronaut walks, they begin to run and eventually leap into the air, floating above the moon's rocky terrain. The scene transitions to the astronaut drifting away from the moon, with the lunar landscape and the moon itself visible in the background. The video concludes with the astronaut continuing to float in space, gazing at the moon.

{
  "completed_at": "2024-12-16T21:19:18.081679Z",
  "created_at": "2024-12-16T21:17:52.370000Z",
  "data_removed": false,
  "error": null,
  "id": "bw7z78n9e9rme0ckt5aszgcf9g",
  "input": {
    "top_p": 0.7,
    "video": "https://replicate.delivery/pbxt/M9kGHuJMeAKZs0eSbaEk6hCc7zqY4Tg94IxWwDpC5hRiuBPY/astro.mp4",
    "prompt": "Describe this video in detail",
    "temperature": 0.4,
    "max_new_tokens": 256
  },
  "logs": "/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\nwarnings.warn(\n/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/torch/utils/checkpoint.py:61: UserWarning: None of the inputs have requires_grad=True. Gradients will be None\nwarnings.warn(\nThe attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.",
  "metrics": {
    "predict_time": 3.133147223,
    "total_time": 85.711679
  },
  "output": "The video features an astronaut in a white spacesuit walking on the moon's surface. The background showcases a large, detailed moon against a starry sky. As the astronaut walks, they begin to run and eventually leap into the air, floating above the moon's rocky terrain. The scene transitions to the astronaut drifting away from the moon, with the lunar landscape and the moon itself visible in the background. The video concludes with the astronaut continuing to float in space, gazing at the moon.",
  "started_at": "2024-12-16T21:19:14.948532Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/bw7z78n9e9rme0ckt5aszgcf9g",
    "cancel": "https://api.replicate.com/v1/predictions/bw7z78n9e9rme0ckt5aszgcf9g/cancel"
  },
  "version": "e282f76d0451b759128be3e8bccfe5ded8f521f4a7d705883e92f837e563f575"
}

Generated in

3.1 seconds

Tweak it Share Report

Run time and cost

This model costs approximately $0.0014 to run on Replicate, or 714 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 2 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.