Instructions to use tner/roberta-large-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/roberta-large-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/roberta-large-conll2003")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/roberta-large-conll2003") model = AutoModelForTokenClassification.from_pretrained("tner/roberta-large-conll2003") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
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{
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"_name_or_path": "
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"architectures": [
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"RobertaForTokenClassification"
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],
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{
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"_name_or_path": "roberta-large-conll2003",
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"architectures": [
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"RobertaForTokenClassification"
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],
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:d9209b8f0b9bee7269c6c02648dd604825e787ac03776ce8335018adcb309d9f
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size 1417408561
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