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lucataco /whisperspeech-small:a453e7a3
This version is disabled.
This version has been disabled because it consistently fails to complete setup.
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/whisperspeech-small
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet 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/whisperspeech-small using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/whisperspeech-small:a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9d",
{
input: {
prompt: "This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer",
speaker: "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg",
language: "en"
}
}
);
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 replicateSet 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 replicateRun lucataco/whisperspeech-small using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/whisperspeech-small:a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9d",
input={
"prompt": "This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer",
"speaker": "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg",
"language": "en"
}
)
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/whisperspeech-small 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": "a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9d",
"input": {
"prompt": "This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer",
"speaker": "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg",
"language": "en"
}
}' \
https://api.replicate.com/v1/predictionsTo 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 cogIf 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/lucataco/whisperspeech-small@sha256:a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9d \
-i 'prompt="This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer"' \
-i 'speaker="https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg"' \
-i 'language="en"'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/lucataco/whisperspeech-small@sha256:a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9dcurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer", "speaker": "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg", "language": "en" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
Output
Video Player is loading.
Current Time 00:00:000
/
Duration 00:00:000
Loaded: 0%
00:00:000
Stream Type LIVE
Remaining Time -00:00:000
1x
- Chapters
- descriptions off, selected
- captions settings, opens captions settings dialog
- captions off, selected
This is a modal window.
The media could not be loaded, either because the server or network failed or because the format is not supported.
Beginning of dialog window. Escape will cancel and close the window.
End of dialog window.
{
"completed_at": "2024-03-05T20:22:14.415406Z",
"created_at": "2024-03-05T20:21:42.777507Z",
"data_removed": false,
"error": null,
"id": "opvceelb4wathfzfvbcghmlaxm",
"input": {
"prompt": "This is the first demo of Whisper Speech, a fully open source text-to-speech model trained by Collabora and Lion on the Juwels supercomputer",
"speaker": "https://upload.wikimedia.org/wikipedia/commons/7/75/Winston_Churchill_-_Be_Ye_Men_of_Valour.ogg",
"language": "en"
},
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"metrics": {
"predict_time": 31.574549,
"total_time": 31.637899
},
"output": "https://replicate.delivery/pbxt/XvuKEW7EBK54L5sQAv0OZF9YnErznzGLorkE7lM8FZf6hpOJA/output.wav",
"started_at": "2024-03-05T20:21:42.840857Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/opvceelb4wathfzfvbcghmlaxm",
"cancel": "https://api.replicate.com/v1/predictions/opvceelb4wathfzfvbcghmlaxm/cancel"
},
"version": "a453e7a3dde7a9041a210a89339a128f8542e45d5172e46b44530cd9a0406e9d"
}Generated in
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|███████████████████---------------------| 48.40% [364/752 00:09<00:10]
|███████████████████---------------------| 49.34% [371/752 00:09<00:09]
|████████████████████--------------------| 50.27% [378/752 00:09<00:09]
|████████████████████--------------------| 51.20% [385/752 00:09<00:09]
|████████████████████--------------------| 52.13% [392/752 00:10<00:09]
|█████████████████████-------------------| 53.06% [399/752 00:10<00:09]
|█████████████████████-------------------| 53.99% [406/752 00:10<00:08]
|█████████████████████-------------------| 54.92% [413/752 00:10<00:08]
|██████████████████████------------------| 55.85% [420/752 00:10<00:08]
|██████████████████████------------------| 56.78% [427/752 00:11<00:08]
|███████████████████████-----------------| 57.71% [434/752 00:11<00:08]
|███████████████████████-----------------| 58.64% [441/752 00:11<00:08]
|███████████████████████-----------------| 59.57% [448/752 00:11<00:07]
|████████████████████████----------------| 60.51% [455/752 00:11<00:07]
|████████████████████████----------------| 61.44% [462/752 00:11<00:07]
|████████████████████████----------------| 62.37% [469/752 00:12<00:07]
|█████████████████████████---------------| 63.30% [476/752 00:12<00:07]
|█████████████████████████---------------| 64.23% [483/752 00:12<00:06]
|██████████████████████████--------------| 65.16% [490/752 00:12<00:06]
|██████████████████████████--------------| 66.09% [497/752 00:12<00:06]
|██████████████████████████--------------| 67.02% [504/752 00:12<00:06]
|███████████████████████████-------------| 67.95% [511/752 00:13<00:06]
|███████████████████████████-------------| 68.88% [518/752 00:13<00:05]
|███████████████████████████-------------| 69.81% [525/752 00:13<00:05]
|████████████████████████████------------| 70.74% [532/752 00:13<00:05]
|████████████████████████████------------| 71.68% [539/752 00:13<00:05]
|█████████████████████████████-----------| 72.61% [546/752 00:13<00:05]
|█████████████████████████████-----------| 73.54% [553/752 00:14<00:05]
|█████████████████████████████-----------| 74.47% [560/752 00:14<00:04]
|██████████████████████████████----------| 75.40% [567/752 00:14<00:04]
|██████████████████████████████----------| 76.33% [574/752 00:14<00:04]
|██████████████████████████████----------| 77.26% [581/752 00:14<00:04]
|███████████████████████████████---------| 78.19% [588/752 00:14<00:04]
|███████████████████████████████---------| 79.12% [595/752 00:15<00:03]
|████████████████████████████████--------| 80.05% [602/752 00:15<00:03]
|████████████████████████████████--------| 80.98% [609/752 00:15<00:03]
|████████████████████████████████--------| 81.91% [616/752 00:15<00:03]
|█████████████████████████████████-------| 82.85% [623/752 00:15<00:03]
|█████████████████████████████████-------| 83.78% [630/752 00:15<00:03]
|█████████████████████████████████-------| 84.71% [637/752 00:16<00:02]
|██████████████████████████████████------| 85.64% [644/752 00:16<00:02]
|██████████████████████████████████------| 86.57% [651/752 00:16<00:02]
|███████████████████████████████████-----| 87.50% [658/752 00:16<00:02]
|███████████████████████████████████-----| 88.43% [665/752 00:16<00:02]
|███████████████████████████████████-----| 89.36% [672/752 00:16<00:02]
|████████████████████████████████████----| 90.29% [679/752 00:17<00:01]
|████████████████████████████████████----| 91.22% [686/752 00:17<00:01]
|████████████████████████████████████----| 92.15% [693/752 00:17<00:01]
|█████████████████████████████████████---| 93.09% [700/752 00:17<00:01]
|█████████████████████████████████████---| 94.02% [707/752 00:17<00:01]
|█████████████████████████████████████---| 94.95% [714/752 00:18<00:00]
|██████████████████████████████████████--| 95.88% [721/752 00:18<00:00]
|██████████████████████████████████████--| 96.81% [728/752 00:18<00:00]
|███████████████████████████████████████-| 97.74% [735/752 00:18<00:00]
|███████████████████████████████████████-| 98.67% [742/752 00:18<00:00]
|███████████████████████████████████████-| 99.60% [749/752 00:18<00:00]
|████████████████████████████████████████| 100.00% [752/752 00:18<00:00]