Feature Extraction
Transformers
Safetensors
resemblyzer
audio
speaker-embedding
speaker-verification
custom_code
Instructions to use prj-beatrice/resemblyzer-torch-native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prj-beatrice/resemblyzer-torch-native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="prj-beatrice/resemblyzer-torch-native", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("prj-beatrice/resemblyzer-torch-native", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ResemblyzerModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "modeling_resemblyzer.ResemblyzerConfig", | |
| "AutoModel": "modeling_resemblyzer.ResemblyzerModel" | |
| }, | |
| "dtype": "float32", | |
| "model_type": "resemblyzer", | |
| "transformers_version": "5.14.1" | |
| } | |