Instructions to use RJuro/SciNERTopic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJuro/SciNERTopic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RJuro/SciNERTopic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RJuro/SciNERTopic") model = AutoModelForTokenClassification.from_pretrained("RJuro/SciNERTopic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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[](https://colab.research.google.com/github/AI-Growth-Lab/SciNerTopic/blob/main/notebooks/Sci_NERTopic.ipynb)
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NER model based on `allenai/scibert_scivocab_cased`
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Fine-tuned using the [SciERC Dataset](http://nlp.cs.washington.edu/sciIE/) to identify scientific terms:
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[](https://colab.research.google.com/github/AI-Growth-Lab/SciNerTopic/blob/main/notebooks/Sci_NERTopic.ipynb)
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NER model based on `allenai/scibert_scivocab_cased`
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Fine-tuned using the [SciERC Dataset](http://nlp.cs.washington.edu/sciIE/) to identify scientific terms:
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