Instructions to use Aadithyak/WHISPERtestmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aadithyak/WHISPERtestmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Aadithyak/WHISPERtestmodel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Aadithyak/WHISPERtestmodel") model = AutoModelForSpeechSeq2Seq.from_pretrained("Aadithyak/WHISPERtestmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Aadithyak/WHISPERtestmodel: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Aadithyak/WHISPERtestmodel/resolve/main/training_args.bin
- Command line
-
hf download hf://Aadithyak/WHISPERtestmodel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Aadithyak/WHISPERtestmodel/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- fe57d2dd654df6c2fb6f54225f46a495fc5f17f34f5d3d21e86475df8dd39c40
- Size of remote file:
- 5.18 kB
- SHA256:
- 955bd4eaaefab3d865c2605e94d1647da589d6f5da478b49156a1913b90eab9e
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