Instructions to use Tengisbold/roberta-base-ner-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tengisbold/roberta-base-ner-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tengisbold/roberta-base-ner-demo")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tengisbold/roberta-base-ner-demo") model = AutoModelForTokenClassification.from_pretrained("Tengisbold/roberta-base-ner-demo") - 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:ae0a26780546f316f1d60355657a8f2c7bc7006c7d760ead39f9c9275addb7e5
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size 496263676
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