Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
hf-asr-leaderboard
Generated from Trainer
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Instructions to use fkapsahili/whisper-small-openslrdev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fkapsahili/whisper-small-openslrdev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fkapsahili/whisper-small-openslrdev")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("fkapsahili/whisper-small-openslrdev") model = AutoModelForSpeechSeq2Seq.from_pretrained("fkapsahili/whisper-small-openslrdev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fkapsahili/whisper-small-openslrdev: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
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https://huggingface.co/fkapsahili/whisper-small-openslrdev/resolve/main/training_args.bin
- Command line
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hf download hf://fkapsahili/whisper-small-openslrdev/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/fkapsahili/whisper-small-openslrdev/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 42d25f254298d2c644dc3d404b5c450e2e837e3adbb3e97e21618882c4f6e3bc
- Size of remote file:
- 5.05 kB
- SHA256:
- 79d914233cd8edb568408aa858b4cb4d19a8e65c90ea52bcf13b866b3b8d8fbe
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