Instructions to use emon1521/wav2vec2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emon1521/wav2vec2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emon1521/wav2vec2-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("emon1521/wav2vec2-base") model = AutoModelForCTC.from_pretrained("emon1521/wav2vec2-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from emon1521/wav2vec2-base: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/emon1521/wav2vec2-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://emon1521/wav2vec2-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/emon1521/wav2vec2-base/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 1021296578221c638553c49659e8ca03c5d79138b34c99333ce677bd05d9bb5e
- Size of remote file:
- 378 MB
- SHA256:
- 855fc30b5566dc4f5fc709224f6f18c2e3a9954fdc3dc096df770539aaa62036
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