Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use mscs23021/Whisper_Small_Final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mscs23021/Whisper_Small_Final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mscs23021/Whisper_Small_Final")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mscs23021/Whisper_Small_Final") model = AutoModelForSpeechSeq2Seq.from_pretrained("mscs23021/Whisper_Small_Final", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mscs23021/Whisper_Small_Final: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/mscs23021/Whisper_Small_Final/resolve/main/training_args.bin
- Command line
-
hf download hf://mscs23021/Whisper_Small_Final/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mscs23021/Whisper_Small_Final/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 11237a98aaf446b51d115b1eb2bff7ab943188e87b86d5c2b7f5648a2652387b
- Size of remote file:
- 5.5 kB
- SHA256:
- a7fa4eed6fe3049eebbaa7627b8afed7bbf7fd0582ffdf63b00bb5be4e120c2d
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