smoretalk / clip-interrogator-turbo

@pharmapsychotic 's CLIP-Interrogator, but 3x faster and more accurate. Specialized on SDXL.

Warm

Public
2.2M runs
L40S

Iterate in playground

Run with an API

Playground API Examples README Versions

Prediction

smoretalk/clip-interrogator-turbo:f66767bbd5c60b841e05dfb72a176d11bf36eca0554c6ea5d6d705cf617bafe8

Model

smoretalk/clip-interrogator-turbo:f66767bb

58wq98gs25rgg0cemjrbw3kj1w

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

3m 8s

Created

about 1 year ago

Input

mode: best
image
style_only

{
  "mode": "best",
  "image": "https://replicate.delivery/pbxt/KgRWg4JUfnnszNV78fo1PMRvYxCD9nCgf26Va4RtLxWcuujW/illust-car.png",
  "style_only": false
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run smoretalk/clip-interrogator-turbo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "smoretalk/clip-interrogator-turbo:f66767bbd5c60b841e05dfb72a176d11bf36eca0554c6ea5d6d705cf617bafe8",
  {
    input: {
      mode: "best",
      image: "https://replicate.delivery/pbxt/KgRWg4JUfnnszNV78fo1PMRvYxCD9nCgf26Va4RtLxWcuujW/illust-car.png",
      style_only: false
    }
  }
);

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

Import the client:

import replicate

Run smoretalk/clip-interrogator-turbo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "smoretalk/clip-interrogator-turbo:f66767bbd5c60b841e05dfb72a176d11bf36eca0554c6ea5d6d705cf617bafe8",
    input={
        "mode": "best",
        "image": "https://replicate.delivery/pbxt/KgRWg4JUfnnszNV78fo1PMRvYxCD9nCgf26Va4RtLxWcuujW/illust-car.png",
        "style_only": False
    }
)
print(output)

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

Run smoretalk/clip-interrogator-turbo 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": "smoretalk/clip-interrogator-turbo:f66767bbd5c60b841e05dfb72a176d11bf36eca0554c6ea5d6d705cf617bafe8",
    "input": {
      "mode": "best",
      "image": "https://replicate.delivery/pbxt/KgRWg4JUfnnszNV78fo1PMRvYxCD9nCgf26Va4RtLxWcuujW/illust-car.png",
      "style_only": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

a painting of a yellow car parked in front of a house with trees in the, by Makoto Shinkai, featured on pixiv, makoto shinkai. high detail, by makoto shinkai, in style of makoto shinkai, makoto shinkai art style, makoto shinkai. —h 2160, anime keyframe

{
  "completed_at": "2024-04-03T16:02:55.865414Z",
  "created_at": "2024-04-03T15:59:47.985000Z",
  "data_removed": false,
  "error": null,
  "id": "58wq98gs25rgg0cemjrbw3kj1w",
  "input": {
    "mode": "best",
    "image": "https://replicate.delivery/pbxt/KgRWg4JUfnnszNV78fo1PMRvYxCD9nCgf26Va4RtLxWcuujW/illust-car.png",
    "style_only": false
  },
  "logs": "Both `max_new_tokens` (=16) and `max_length`(=212) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n/root/.pyenv/versions/3.11.9/lib/python3.11/site-packages/transformers/generation/utils.py:1156: UserWarning: Unfeasible length constraints: `min_length` (37) is larger than the maximum possible length (16). Generation will stop at the defined maximum length. You should decrease the minimum length and/or increase the maximum length.\nwarnings.warn(\nFinish generating a caption in 1.91 seconds.\nUnused or unrecognized kwargs: padding.\nUnused or unrecognized kwargs: padding.\nFinish generating an image embedding in 0.23 seconds.\nFinish generating a text embedding in 0.15 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.15 seconds.\nFinish generating a text embedding in 0.15 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.15 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.14 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.13 seconds.\nFinish generating a text embedding in 0.15 seconds.\nFinish generating a text embedding in 0.13 seconds.\nBest prompt is 'a painting of a yellow car parked in front of a house with trees in the, by Makoto Shinkai, featured on pixiv, makoto shinkai. high detail,  by makoto shinkai,  in style of makoto shinkai,  makoto shinkai art style,  makoto shinkai. —h 2160,  anime keyframe'.\nFinish generating a prompt in 8.34 seconds.",
  "metrics": {
    "predict_time": 9.309009,
    "total_time": 187.880414
  },
  "output": "a painting of a yellow car parked in front of a house with trees in the, by Makoto Shinkai, featured on pixiv, makoto shinkai. high detail, by makoto shinkai, in style of makoto shinkai, makoto shinkai art style, makoto shinkai. —h 2160, anime keyframe",
  "started_at": "2024-04-03T16:02:46.556405Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/58wq98gs25rgg0cemjrbw3kj1w",
    "cancel": "https://api.replicate.com/v1/predictions/58wq98gs25rgg0cemjrbw3kj1w/cancel"
  },
  "version": "f66767bbd5c60b841e05dfb72a176d11bf36eca0554c6ea5d6d705cf617bafe8"
}

Generated in

9.3 seconds

Tweak it Share Report

Both `max_new_tokens` (=16) and `max_length`(=212) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)
/root/.pyenv/versions/3.11.9/lib/python3.11/site-packages/transformers/generation/utils.py:1156: UserWarning: Unfeasible length constraints: `min_length` (37) is larger than the maximum possible length (16). Generation will stop at the defined maximum length. You should decrease the minimum length and/or increase the maximum length.
warnings.warn(
Finish generating a caption in 1.91 seconds.
Unused or unrecognized kwargs: padding.
Unused or unrecognized kwargs: padding.
Finish generating an image embedding in 0.23 seconds.
Finish generating a text embedding in 0.15 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.15 seconds.
Finish generating a text embedding in 0.15 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.15 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.14 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.13 seconds.
Finish generating a text embedding in 0.15 seconds.
Finish generating a text embedding in 0.13 seconds.
Best prompt is 'a painting of a yellow car parked in front of a house with trees in the, by Makoto Shinkai, featured on pixiv, makoto shinkai. high detail,  by makoto shinkai,  in style of makoto shinkai,  makoto shinkai art style,  makoto shinkai. —h 2160,  anime keyframe'.
Finish generating a prompt in 8.34 seconds.

Want to make some of these yourself?

Run this model