Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use arsonor/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arsonor/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arsonor/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arsonor/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("arsonor/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arsonor/whisper-tiny-en: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/arsonor/whisper-tiny-en/resolve/main/training_args.bin
- Command line
-
hf download hf://arsonor/whisper-tiny-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arsonor/whisper-tiny-en/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 0a0d21355ac7f9e05a7ac2a17d57a5897010485f27a316da87ac2e752a5c67b7
- Size of remote file:
- 5.43 kB
- SHA256:
- acc60d20a845eb09d55cea1fdf28f2765918005f8e90e5f707c5c3edf7299ad1
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