Feature Extraction
Transformers
PyTorch
Safetensors
hubert
speech processing
self-supervision
african languages
🇪🇺 Region: EU
Instructions to use Orange/SSA-HuBERT-base-5k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Orange/SSA-HuBERT-base-5k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Orange/SSA-HuBERT-base-5k")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Orange/SSA-HuBERT-base-5k") model = AutoModel.from_pretrained("Orange/SSA-HuBERT-base-5k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e91f17be20744d20e3464f3625aa358f8c896e8077dd8aa4c505c0158ff440a3
- Size of remote file:
- 378 MB
- SHA256:
- 22695e22072c870eace15a02271584d48261d7d00515634fd9f6bde00e32bfbf
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