Instructions to use bkh6722/bach-arb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bkh6722/bach-arb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bkh6722/bach-arb")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("bkh6722/bach-arb") model = AutoModelForCTC.from_pretrained("bkh6722/bach-arb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bkh6722/bach-arb: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/bkh6722/bach-arb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bkh6722/bach-arb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bkh6722/bach-arb/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- a170e5d07b14476a4b54c306d5cdbcd7cf7f575256951bc2228b6c5d6139cb3f
- Size of remote file:
- 378 MB
- SHA256:
- ac09e99b5b78ab5299caaddc40f90ac4dd74a31e11c01b7f786a9e4d0b39946c
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