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 pytorch_model.bin from Raffay/speech_processing_project_wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Raffay/speech_processing_project_wav2vec2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Raffay/speech_processing_project_wav2vec2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Raffay/speech_processing_project_wav2vec2/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 20f5c27f3ca81076445d9a32a8eacee101ddbb91b4b3ebe17fd446ddfa9190d0
- Size of remote file:
- 378 MB
- SHA256:
- 895f53bc0fc639d7fe62d539a0640d7ab4f04dcd8636e8f9c0164301d0b7b41e
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