Instructions to use 202015004/Spoof_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 202015004/Spoof_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="202015004/Spoof_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("202015004/Spoof_detection") model = AutoModelForCTC.from_pretrained("202015004/Spoof_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 202015004/Spoof_detection: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/202015004/Spoof_detection/resolve/main/training_args.bin
- Command line
-
hf download hf://202015004/Spoof_detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/202015004/Spoof_detection/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- baec305a895f228212eb279252ea9bbfdcce3162499797933f1dcc2de414f991
- Size of remote file:
- 2.99 kB
- SHA256:
- fe808847ff7fa4b18ce47eba06568c7b035cfc236b0f6e008e057d494c4c6a5f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.