Instructions to use skadio/ner4opt-roberta-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skadio/ner4opt-roberta-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="skadio/ner4opt-roberta-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("skadio/ner4opt-roberta-v1") model = AutoModelForTokenClassification.from_pretrained("skadio/ner4opt-roberta-v1") - Notebooks
- Google Colab
- Kaggle
Ner4Opt: Named Entity Recognition for Optimization
Given an optimization problem in natural language, Ner4Opt extracts optimization related entities from free-form text.
This Ner4Opt model is fine-tuned on optimization specific corpora.
See the Ner4Opt library and model details.
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