Instructions to use classla/wav2vec2-large-slavic-parlaspeech-hr-lm 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-lm 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-lm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("classla/wav2vec2-large-slavic-parlaspeech-hr-lm") model = AutoModelForCTC.from_pretrained("classla/wav2vec2-large-slavic-parlaspeech-hr-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from classla/wav2vec2-large-slavic-parlaspeech-hr-lm: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/classla/wav2vec2-large-slavic-parlaspeech-hr-lm/resolve/e1a084f509be3bab50014f2fd920ef6c1ef0e1dc/pytorch_model.bin
- Command line
-
hf download hf://classla/wav2vec2-large-slavic-parlaspeech-hr-lm@e1a084f509be3bab50014f2fd920ef6c1ef0e1dc/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/classla/wav2vec2-large-slavic-parlaspeech-hr-lm/resolve/e1a084f509be3bab50014f2fd920ef6c1ef0e1dc/pytorch_model.bin
1.26 GB
- Xet hash:
- 1213c0cc70db762cfaefbd275d7b67b74a9b3db0c8a53a0af5d37bebd8b55eb2
- Size of remote file:
- 1.26 GB
- SHA256:
- da283860a36a55709c5a3836ef8ba1afbc02c7e49c1534d78de44f97c8f15be2
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