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
File size: 166 Bytes
6f980ab | 1 2 3 4 5 6 7 | {
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"sampling_rate": 16000,
"do_normalize": true,
"padding_value": 0.0,
"return_attention_mask": false
} |