Feature Extraction
Transformers
PyTorch
English
distilled_speech
speech
audio
data2vec
distillation
custom_code
Instructions to use TuKoResearch/AuriStreamDistillLarge_100M40PredTeacher_bad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TuKoResearch/AuriStreamDistillLarge_100M40PredTeacher_bad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="TuKoResearch/AuriStreamDistillLarge_100M40PredTeacher_bad", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TuKoResearch/AuriStreamDistillLarge_100M40PredTeacher_bad", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4a474e72b10fcacaed3d7fd60279ca56623dd1657c9547f0987db17b0155506
- Size of remote file:
- 1.23 GB
- SHA256:
- ca6b28036a2f7f29938d1228deadc8ef6ae4ebd4b2d5de65f54f89a7edb36a5b
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