Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
Lule Sami
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/salmon-whisper-large-smj-lr7e-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/salmon-whisper-large-smj-lr7e-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/salmon-whisper-large-smj-lr7e-5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/salmon-whisper-large-smj-lr7e-5") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/salmon-whisper-large-smj-lr7e-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9eefc4126a95b14a4e76285358c483229689885b3176f3c1dcaad3f9651068b
- Size of remote file:
- 3.09 GB
- SHA256:
- 2236383a3bcefa8ba02e3d456b87f9c3ed196f68a5aa760720f736f2a6544b55
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