Instructions to use Qasim30/ner_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qasim30/ner_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Qasim30/ner_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Qasim30/ner_bert") model = AutoModelForTokenClassification.from_pretrained("Qasim30/ner_bert") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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 sha256:86b0a5917df447f352601e128985ceb563226c969ed1ff63d558cb9a2f68a6d5
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size 435642228
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