Instructions to use darinchau/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darinchau/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="darinchau/checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("darinchau/checkpoints") model = AutoModelForSpeechSeq2Seq.from_pretrained("darinchau/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from darinchau/checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/darinchau/checkpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://darinchau/checkpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/darinchau/checkpoints/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- a8daa952e2533dcfb258f639b769941c6db21b07dd9d40e15be3ee750ac8678e
- Size of remote file:
- 4.86 kB
- SHA256:
- 8f643ea676d25806df8abf58f0cac08eec1f5508b8c66f2930d29ee87ab088f9
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