Instructions to use MU-NLPC/ner-gazetteers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MU-NLPC/ner-gazetteers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MU-NLPC/ner-gazetteers")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MU-NLPC/ner-gazetteers") model = AutoModelForTokenClassification.from_pretrained("MU-NLPC/ner-gazetteers", device_map="auto") - 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 sha256:92073fe2a66db68bbdb8a665cb69d6f62d23fa72d0ff3a4704b0b5b067a68ec1
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size 501586408
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