Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use explorer7/whisper-tiny-minds14-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use explorer7/whisper-tiny-minds14-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="explorer7/whisper-tiny-minds14-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("explorer7/whisper-tiny-minds14-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("explorer7/whisper-tiny-minds14-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from explorer7/whisper-tiny-minds14-en: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/explorer7/whisper-tiny-minds14-en/resolve/main/training_args.bin
- Command line
-
hf download hf://explorer7/whisper-tiny-minds14-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/explorer7/whisper-tiny-minds14-en/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 1e477b042757aaf2fe48fdf0785c2296c76f588dc42f75847f3fa255e57ec00d
- Size of remote file:
- 5.33 kB
- SHA256:
- da33ed4c082af0e468d3709c7642cac824c86e1eb7ca2be64665c54b827befdb
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