Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Hebrew
wav2vec2
Generated from Trainer
robust-speech-event
Instructions to use imvladikon/wav2vec2-xls-r-300m-lm-hebrew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imvladikon/wav2vec2-xls-r-300m-lm-hebrew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="imvladikon/wav2vec2-xls-r-300m-lm-hebrew")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("imvladikon/wav2vec2-xls-r-300m-lm-hebrew") model = AutoModelForCTC.from_pretrained("imvladikon/wav2vec2-xls-r-300m-lm-hebrew", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"labels": [" ", "\u05d0", "\u05d1", "\u05d2", "\u05d3", "\u05d4", "\u05d5", "\u05d6", "\u05d7", "\u05d8", "\u05d9", "\u05da", "\u05db", "\u05dc", "\u05dd", "\u05de", "\u05df", "\u05e0", "\u05e1", "\u05e2", "\u05e3", "\u05e4", "\u05e5", "\u05e6", "\u05e7", "\u05e8", "\u05e9", "\u05ea", "\u2047", "", "<s>", "</s>"], "is_bpe": false} |