Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use benjipeng/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjipeng/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="benjipeng/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("benjipeng/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("benjipeng/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Nov06_13-31-11_sagemaker-data-scienc-ml-g5-xlarge-997f2666105bc59860062d09e89d
- Nov06_13-53-38_sagemaker-data-scienc-ml-g5-xlarge-997f2666105bc59860062d09e89d
- Nov06_13-54-48_sagemaker-data-scienc-ml-g5-xlarge-997f2666105bc59860062d09e89d
- Nov06_14-28-29_pytorch-2-0-1-gpu-py3-ml-g5-xlarge-322a68844a891daaff0ca7d41bac
- Nov06_15-06-47_pytorch-2-0-1-gpu-py3-ml-g5-xlarge-322a68844a891daaff0ca7d41bac