Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use keess/whisper-model-internal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keess/whisper-model-internal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="keess/whisper-model-internal")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("keess/whisper-model-internal") model = AutoModelForSpeechSeq2Seq.from_pretrained("keess/whisper-model-internal") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened about 1 year ago
by
SFconvertbot