Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use team4/whisperEN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team4/whisperEN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="team4/whisperEN")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("team4/whisperEN") model = AutoModelForSpeechSeq2Seq.from_pretrained("team4/whisperEN", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from team4/whisperEN: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/team4/whisperEN/resolve/main/training_args.bin
- Command line
-
hf download hf://team4/whisperEN/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/team4/whisperEN/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- c287c7b8553927a517c7b15f8125d0138f0848f968b86a38d81a39a5b0cea509
- Size of remote file:
- 5.05 kB
- SHA256:
- 53b43af443b99882c0b7aa35e2b73ac3a5f0325cc9b5ec1c0fa2138a9a9db466
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