Instructions to use hiba2/mms_40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiba2/mms_40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hiba2/mms_40")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hiba2/mms_40") model = AutoModelForCTC.from_pretrained("hiba2/mms_40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hiba2/mms_40: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/hiba2/mms_40/resolve/main/training_args.bin
- Command line
-
hf download hf://hiba2/mms_40/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hiba2/mms_40/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- e1ec17c296e4c845e37760155e4038883136f77f4aa8dac9df9c2aa2b4de0d29
- Size of remote file:
- 4.73 kB
- SHA256:
- 64f41737917c4463bf31ca8cea2bb469bfc07ada5b5eee22ea2bc1f3cb814621
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