Feature Extraction
Transformers
PyTorch
English
distilled_speech
speech
audio
data2vec
distillation
custom_code
Instructions to use TuKoResearch/AuriStreamDistill_100M40PredTeacher_librispeech960 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TuKoResearch/AuriStreamDistill_100M40PredTeacher_librispeech960 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="TuKoResearch/AuriStreamDistill_100M40PredTeacher_librispeech960", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TuKoResearch/AuriStreamDistill_100M40PredTeacher_librispeech960", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 387d1e61c9cdf54ea636bad7ba2a13222171a944cd5f8fc697cd13a36bb5606b
- Size of remote file:
- 359 MB
- SHA256:
- 5d818dc5701dedd635879dcc3a5df3056714f5f53ba80d90d11843e9b62fdc3d
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