Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Ihssane123/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ihssane123/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ihssane123/whisper-tiny-en-US")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Ihssane123/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("Ihssane123/whisper-tiny-en-US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ihssane123/whisper-tiny-en-US: direct link, hf CLI and curl.
- Browser
- Download file 5.97 kB
-
https://huggingface.co/Ihssane123/whisper-tiny-en-US/resolve/main/training_args.bin
- Command line
-
hf download hf://Ihssane123/whisper-tiny-en-US/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ihssane123/whisper-tiny-en-US/resolve/main/training_args.bin
5.97 kB
- Xet hash:
- 8f5a258accda7a228b83c46d45af5f34c0d11b188ca114164332507f12e16550
- Size of remote file:
- 5.97 kB
- SHA256:
- 2026a16d59a86d6cd57795d3bafcb0ce5e88a0174c318e29869052c90a4b3841
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