Instructions to use marcsixtysix/whisper-tiny-pl03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcsixtysix/whisper-tiny-pl03 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marcsixtysix/whisper-tiny-pl03")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("marcsixtysix/whisper-tiny-pl03") model = AutoModelForSpeechSeq2Seq.from_pretrained("marcsixtysix/whisper-tiny-pl03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
language:
- pl
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
model-index:
- name: Whisper Small PL
results: []
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0