Instructions to use pinot/wav2vec2-test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pinot/wav2vec2-test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pinot/wav2vec2-test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("pinot/wav2vec2-test2") model = AutoModelForCTC.from_pretrained("pinot/wav2vec2-test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pinot/wav2vec2-test2: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/pinot/wav2vec2-test2/resolve/main/training_args.bin
- Command line
-
hf download hf://pinot/wav2vec2-test2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pinot/wav2vec2-test2/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 02c759350bc303d56e82b9eb47359eea1e50e9aa415ef8fa92524c2d78a029b3
- Size of remote file:
- 4.03 kB
- SHA256:
- 75edd8d446072c6f2d9c4a429dc6a5a21edb535c2cd04f1e0a96743e84f43b07
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