Instructions to use kinit/slovakbert-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kinit/slovakbert-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kinit/slovakbert-pos")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kinit/slovakbert-pos") model = AutoModelForTokenClassification.from_pretrained("kinit/slovakbert-pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kinit/slovakbert-pos: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/kinit/slovakbert-pos/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kinit/slovakbert-pos/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kinit/slovakbert-pos/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- cce200c845debb8a7ade9c6a245b802a5550f164461b397819f4bca1338d2d3f
- Size of remote file:
- 496 MB
- SHA256:
- 11162771dd7dda3eeb128c9f72a86fa19d833e7e2fa87ee7b453aa2f4e2bbdef
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