Feature Extraction
Transformers
PyTorch
Safetensors
hubert
speech processing
self-supervision
african languages
🇪🇺 Region: EU
Instructions to use Orange/SSA-HuBERT-base-60k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Orange/SSA-HuBERT-base-60k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Orange/SSA-HuBERT-base-60k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Orange/SSA-HuBERT-base-60k") model = AutoModel.from_pretrained("Orange/SSA-HuBERT-base-60k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de69b51bb401f2e05244d889194fb6ac39fc6960ab7f937b2b4ae57f5b606359
- Size of remote file:
- 378 MB
- SHA256:
- 5a0bab94d962f6267d4224c5d29c78d635f7679c201aa51264d586c26fbb8c0c
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