Instructions to use classla/wav2vec2-large-slavic-parlaspeech-hr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/wav2vec2-large-slavic-parlaspeech-hr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="classla/wav2vec2-large-slavic-parlaspeech-hr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("classla/wav2vec2-large-slavic-parlaspeech-hr") model = AutoModelForCTC.from_pretrained("classla/wav2vec2-large-slavic-parlaspeech-hr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 611ec429282da103ddcbd78ff72b3f0510baaf90b02d9844e5f4473f09e4907f
- Size of remote file:
- 1.26 GB
- SHA256:
- d63fe4ba631c09a2b60c483cbdcd417de529d31722f73c7af0aed326d66d92f5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.