Instructions to use GraphBot/model-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GraphBot/model-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="GraphBot/model-pt")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("GraphBot/model-pt") model = AutoModelForTokenClassification.from_pretrained("GraphBot/model-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
tags: []
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# Model Card for Model ID
This is a Natural Entity Recognition Model built to recognise variable names and graph types for use in a bioinformatics graphing tool.
It was build by Sarina Chai, Daichi Ito and Harry Martens as part of a UNSW DESN2000 Project
The model is built upon the existing BERT-BASED-UNCASED model. |