Instructions to use Raffay/speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/speech_processing_project_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Raffay/speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Raffay/speech_processing_project_wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/Raffay/speech_processing_project_wav2vec2/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Raffay/speech_processing_project_wav2vec2@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Raffay/speech_processing_project_wav2vec2/resolve/refs%2Fpr%2F1/training_args.bin
3.12 kB
- Xet hash:
- 1b5fede16cd644ff19c49ad5e388ee5de78d4e6563aeab36f6b896ba32f9f4ad
- Size of remote file:
- 3.12 kB
- SHA256:
- f39c4b2cf1e16e9610b41335775ed948d8a895dcded05028f27e5238af5965e2
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