Instructions to use emon1521/wav2vec2-try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emon1521/wav2vec2-try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emon1521/wav2vec2-try")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("emon1521/wav2vec2-try") model = AutoModelForCTC.from_pretrained("emon1521/wav2vec2-try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download dev-clean.tar.gz from emon1521/wav2vec2-try: direct link, hf CLI and curl.
- Browser
- Download file 338 MB
-
https://huggingface.co/emon1521/wav2vec2-try/resolve/main/dev-clean.tar.gz
- Command line
-
hf download hf://emon1521/wav2vec2-try/dev-clean.tar.gz
-
curl -L -o dev-clean.tar.gz https://huggingface.co/emon1521/wav2vec2-try/resolve/main/dev-clean.tar.gz
338 MB
- Xet hash:
- d2da2f8226da4eae12aa3fb9150d3b67c538080012bb444cc4a49e6d288a2b6f
- Size of remote file:
- 338 MB
- SHA256:
- 76f87d090650617fca0cac8f88b9416e0ebf80350acb97b343a85fa903728ab3
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