Instructions to use HamdanXI/Wav2vec2_MyST_Train_and_Dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HamdanXI/Wav2vec2_MyST_Train_and_Dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="HamdanXI/Wav2vec2_MyST_Train_and_Dev")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("HamdanXI/Wav2vec2_MyST_Train_and_Dev") model = AutoModelForCTC.from_pretrained("HamdanXI/Wav2vec2_MyST_Train_and_Dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HamdanXI/Wav2vec2_MyST_Train_and_Dev: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/HamdanXI/Wav2vec2_MyST_Train_and_Dev/resolve/main/training_args.bin
- Command line
-
hf download hf://HamdanXI/Wav2vec2_MyST_Train_and_Dev/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HamdanXI/Wav2vec2_MyST_Train_and_Dev/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 2bbcae6695a78bedf727c4de4963e90d82023f66a8ccf4b1fca446d639141a5b
- Size of remote file:
- 5.78 kB
- SHA256:
- 04ee7c30e5509175f108f84e09109aa8299d2ebf0ada9c9b5774eb439efdd152
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