Instructions to use Buseak/vowelizer_1203_v8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Buseak/vowelizer_1203_v8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Buseak/vowelizer_1203_v8")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Buseak/vowelizer_1203_v8") model = AutoModelForTokenClassification.from_pretrained("Buseak/vowelizer_1203_v8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Buseak/vowelizer_1203_v8: direct link, hf CLI and curl.
- Browser
- Download file 529 MB
-
https://huggingface.co/Buseak/vowelizer_1203_v8/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Buseak/vowelizer_1203_v8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Buseak/vowelizer_1203_v8/resolve/main/pytorch_model.bin
529 MB
- Xet hash:
- b93feb0a17369871d37887494d1501f4a2635995e0bdf6317e6504fccbc02b5b
- Size of remote file:
- 529 MB
- SHA256:
- 74f253b89174add0ced6cced1b5354e6aed482cd1e19871551a2c2f47dd63cf7
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