Instructions to use MagicLuke/ecapa-tdnn-speaker-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MagicLuke/ecapa-tdnn-speaker-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MagicLuke/ecapa-tdnn-speaker-encoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MagicLuke/ecapa-tdnn-speaker-encoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from MagicLuke/ecapa-tdnn-speaker-encoder: direct link, hf CLI and curl.
- Browser
- Download file 154 Bytes
-
https://huggingface.co/MagicLuke/ecapa-tdnn-speaker-encoder/resolve/8d94934b5251345d30ffef78e9afdb6a03fb6186/config.json
- Command line
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hf download hf://MagicLuke/ecapa-tdnn-speaker-encoder@8d94934b5251345d30ffef78e9afdb6a03fb6186/config.json
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curl -L -o config.json https://huggingface.co/MagicLuke/ecapa-tdnn-speaker-encoder/resolve/8d94934b5251345d30ffef78e9afdb6a03fb6186/config.json
154 Bytes
| { | |
| "C": 1024, | |
| "architectures": [ | |
| "HFECAPATDNN" | |
| ], | |
| "model_type": "ecapa_tdnn", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.49.0" | |
| } | |