Instructions to use MariaK/whisper-tiny-minds-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MariaK/whisper-tiny-minds-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MariaK/whisper-tiny-minds-v1")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("MariaK/whisper-tiny-minds-v1") model = AutoModelForSpeechSeq2Seq.from_pretrained("MariaK/whisper-tiny-minds-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f0986733734f0701d20035bbd1c278252cbd0758074c9e0175233725dcf47b1
- Size of remote file:
- 151 MB
- SHA256:
- e1425f99116b9cc79cc9214fa9598d0ba00efd923021ae9d25adcc675867056f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.