Instructions to use paxstan/wav2vec2-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paxstan/wav2vec2-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="paxstan/wav2vec2-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("paxstan/wav2vec2-test") model = AutoModelForCTC.from_pretrained("paxstan/wav2vec2-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from paxstan/wav2vec2-test: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/paxstan/wav2vec2-test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://paxstan/wav2vec2-test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/paxstan/wav2vec2-test/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 349a3edec6807208bd4e59c79d9c68ee23754baf3641703b589b12d0c5ad9246
- Size of remote file:
- 378 MB
- SHA256:
- 4d8ca07e7332d68ae8a63dec8de13947e8e4c70d260d9768782b383dca3bfb8c
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