Instructions to use Aspik101/distil-whisper-large-v3-pl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aspik101/distil-whisper-large-v3-pl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Aspik101/distil-whisper-large-v3-pl")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Aspik101/distil-whisper-large-v3-pl") model = AutoModelForSpeechSeq2Seq.from_pretrained("Aspik101/distil-whisper-large-v3-pl", device_map="auto") - Transformers.js
How to use Aspik101/distil-whisper-large-v3-pl with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'Aspik101/distil-whisper-large-v3-pl'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 621f4dc42a35abbffa40b3364e7680670032b94a66f103b9b4ce2c3d0d8da707
- Size of remote file:
- 1.06 kB
- SHA256:
- 5c3be033a6214468e6ecbf76cea3bc6258a8837eb1e2ce65571bc936fd008dcc
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