Instructions to use voidful/hubert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voidful/hubert-tiny")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("voidful/hubert-tiny") model = AutoModel.from_pretrained("voidful/hubert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 213 Bytes
d6c348e | 1 2 3 4 5 6 7 8 9 | {
"do_normalize": false,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0,
"return_attention_mask": false,
"sampling_rate": 16000
} |