Instructions to use Raffay/v1_speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/v1_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/v1_speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/v1_speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/v1_speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Raffay/v1_speech_processing_project_wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Raffay/v1_speech_processing_project_wav2vec2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Raffay/v1_speech_processing_project_wav2vec2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Raffay/v1_speech_processing_project_wav2vec2/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 1d99729b058b3c30d5ada47bca2f5d89977a09adeb112de1d39be3bcb14d0764
- Size of remote file:
- 1.26 GB
- SHA256:
- c46081ce69467cbb18119f4aee6ad0a067d7778b93c8fa07c62a8fd1bcb2c2c4
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