Instructions to use zagibest/roberta-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zagibest/roberta-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="zagibest/roberta-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("zagibest/roberta-base-ner") model = AutoModelForTokenClassification.from_pretrained("zagibest/roberta-base-ner") - 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:da0a7b2f03bfbf62a2820c75c4ef3cb4fd7058c5ab14d3cd26191692f6e0797f
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size 496263676
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