Automatic Speech Recognition
Transformers
JAX
TensorBoard
Norwegian
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabArchive/scream_tertius_dropout_replicate_test7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/scream_tertius_dropout_replicate_test7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabArchive/scream_tertius_dropout_replicate_test7b")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabArchive/scream_tertius_dropout_replicate_test7b") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabArchive/scream_tertius_dropout_replicate_test7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0b5a0f36f6aa884951bd5dd28333986bc4ff456b6980d29a22ba192aca02f13
- Size of remote file:
- 3.1 kB
- SHA256:
- 3ba4c817d532d529d85f384c223f10589f4944bdf1b693a78afd78b5ea96148a
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