Instructions to use classla/wav2vec2-xls-r-parlaspeech-hr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/wav2vec2-xls-r-parlaspeech-hr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="classla/wav2vec2-xls-r-parlaspeech-hr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("classla/wav2vec2-xls-r-parlaspeech-hr") model = AutoModelForCTC.from_pretrained("classla/wav2vec2-xls-r-parlaspeech-hr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from classla/wav2vec2-xls-r-parlaspeech-hr: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/classla/wav2vec2-xls-r-parlaspeech-hr/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://classla/wav2vec2-xls-r-parlaspeech-hr/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/classla/wav2vec2-xls-r-parlaspeech-hr/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 6e30ab73218d2c86a32fd35396b48e4765aa0bfee8f12b6941f8c122bfac6b93
- Size of remote file:
- 1.26 GB
- SHA256:
- a8832802a6f0497cac9b5409e1fbc323395d51b9df11522d9b57921ec8537ef6
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