Instructions to use Nargizi/screeve-postagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nargizi/screeve-postagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Nargizi/screeve-postagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Nargizi/screeve-postagger") model = AutoModelForTokenClassification.from_pretrained("Nargizi/screeve-postagger") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:72d3bb16b57ebba59ba283e756b680f5491c9e1ef21cfc2e0dd68051ca3094b4
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size 1726932
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