Instructions to use SinQQQ/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinQQQ/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SinQQQ/content")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SinQQQ/content") model = AutoModelForSpeechSeq2Seq.from_pretrained("SinQQQ/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SinQQQ/content: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/SinQQQ/content/resolve/main/training_args.bin
- Command line
-
hf download hf://SinQQQ/content/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SinQQQ/content/resolve/main/training_args.bin
4.35 kB
- Xet hash:
- a3c771512b5ebfaecd3f3ce69dcb975713350575f6a238f4035e911f30bd9404
- Size of remote file:
- 4.35 kB
- SHA256:
- 9b9e99e4abbc62952ff50e75f567a9e768af05eb4a379bb97074a1ed7b62d52b
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