Instructions to use vilsonrodrigues/fast-pyannote-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vilsonrodrigues/fast-pyannote-embedding with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vilsonrodrigues/fast-pyannote-embedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_cuda.ts from vilsonrodrigues/fast-pyannote-embedding: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/vilsonrodrigues/fast-pyannote-embedding/resolve/main/model_cuda.ts
- Command line
-
hf download hf://vilsonrodrigues/fast-pyannote-embedding/model_cuda.ts
-
curl -L -o model_cuda.ts https://huggingface.co/vilsonrodrigues/fast-pyannote-embedding/resolve/main/model_cuda.ts
17.5 MB
- Xet hash:
- ca5782821e1437eed2a190a1d6c8f78a7d993a5082e0bcc23fb2455f2ff133dc
- Size of remote file:
- 17.5 MB
- SHA256:
- d97c85f4fca50719b852d0720a9b93ea04981d2142fd8a98f6444d90814bc29d
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