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 training_args.bin from emon1521/wav2vec2-base: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/emon1521/wav2vec2-base/resolve/main/training_args.bin
- Command line
-
hf download hf://emon1521/wav2vec2-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/emon1521/wav2vec2-base/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- 9c46e4e1541867107e79e9f872df56abc2f45d8a1cab800d283638fa82dcbcda
- Size of remote file:
- 2.8 kB
- SHA256:
- aa935aa81f17a3358e6ef9ab1460cd83a55c2a2066ebaa5d481933862c2a3fe5
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