suminhthanh/whisperx-custom – Run with an API on Replicate

suminhthanh / whisperx-custom

Cold

Public
1.2K runs
L40S

Run with an API

Playground API Examples README Versions

Input

audio_file

file

Audio file

url

string

Shift + Return to add a new line

URL of the audio file (if audio_file is not provided)

language

string

Shift + Return to add a new line

ISO code of the language spoken in the audio, specify None to perform language detection

language_detection_min_prob

number

If language is not specified, then the language will be detected recursively on different parts of the file until it reaches the given probability

Default: 0

language_detection_max_tries

integer

If language is not specified, then the language will be detected following the logic of language_detection_min_prob parameter, but will stop after the given max retries. If max retries is reached, the most probable language is kept.

Default: 5

initial_prompt

string

Shift + Return to add a new line

Optional text to provide as a prompt for the first window

batch_size

integer

Parallelization of input audio transcription

Default: 64

temperature

number

Temperature to use for sampling

Default: 0

vad_onset

number

VAD onset

Default: 0.5

vad_offset

number

VAD offset

Default: 0.363

align_output

boolean

Aligns whisper output to get accurate word-level timestamps

Default: false

diarization

boolean

Assign speaker ID labels

Default: false

huggingface_access_token

string

Shift + Return to add a new line

To enable diarization, please enter your HuggingFace token (read). You need to accept the user agreement for the models specified in the README.

min_speakers

integer

Minimum number of speakers if diarization is activated (leave blank if unknown)

max_speakers

integer

Maximum number of speakers if diarization is activated (leave blank if unknown)

debug

boolean

Print out compute/inference times and memory usage information

Default: false

keep_audio

boolean

Keep the downloaded audio file

Default: false

openai_api_key

string

Shift + Return to add a new line

OpenAI API key

is_get_video_info

boolean

Get video info

Default: false

cleanup_voice

boolean

Cleanup voice

Default: false

deep_filter

boolean

Deep filter

Default: false

chunk_size

integer

Chunk size

Default: 4

cdn_upload_url

string

Shift + Return to add a new line

CDN UPLOAD URL

cdn_download_url

string

Shift + Return to add a new line

CDN DOWNLOAD URL

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

npx create-replicate --model=suminhthanh/whisperx-custom

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 suminhthanh/whisperx-custom using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "suminhthanh/whisperx-custom:ee4cce7e817c4fb3af359ab6069973ec21855362c3886ae41b0eeed62ff66870",
  {
    input: {
      debug: false,
      vad_onset: 0.5,
      batch_size: 64,
      chunk_size: 4,
      keep_audio: false,
      vad_offset: 0.363,
      deep_filter: false,
      diarization: false,
      temperature: 0,
      align_output: false,
      cleanup_voice: false,
      is_get_video_info: false,
      language_detection_min_prob: 0,
      language_detection_max_tries: 5
    }
  }
);

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 suminhthanh/whisperx-custom using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "suminhthanh/whisperx-custom:ee4cce7e817c4fb3af359ab6069973ec21855362c3886ae41b0eeed62ff66870",
    input={
        "debug": False,
        "vad_onset": 0.5,
        "batch_size": 64,
        "chunk_size": 4,
        "keep_audio": False,
        "vad_offset": 0.363,
        "deep_filter": False,
        "diarization": False,
        "temperature": 0,
        "align_output": False,
        "cleanup_voice": False,
        "is_get_video_info": False,
        "language_detection_min_prob": 0,
        "language_detection_max_tries": 5
    }
)
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 suminhthanh/whisperx-custom 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": "suminhthanh/whisperx-custom:ee4cce7e817c4fb3af359ab6069973ec21855362c3886ae41b0eeed62ff66870",
    "input": {
      "debug": false,
      "vad_onset": 0.5,
      "batch_size": 64,
      "chunk_size": 4,
      "keep_audio": false,
      "vad_offset": 0.363,
      "deep_filter": false,
      "diarization": false,
      "temperature": 0,
      "align_output": false,
      "cleanup_voice": false,
      "is_get_video_info": false,
      "language_detection_min_prob": 0,
      "language_detection_max_tries": 5
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.