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:
- 8f0a03ed7c65f6eae9182845596f72b11de2897853a4a58d062d943366f1ffc8
- Size of remote file:
- 3.09 GB
- SHA256:
- 41607788c19e92622ddef00eb8e60c15a20a3fbb252b0d65ecf18a2b95ba32fc
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