Instructions to use vikash06/idmotif with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikash06/idmotif with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vikash06/idmotif")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vikash06/idmotif") model = AutoModelForSequenceClassification.from_pretrained("vikash06/idmotif") - Notebooks
- Google Colab
- Kaggle
The model finetuned on BERT for classifying cas1 protein sequences and is directly related to the below paper:
@ARTICLE{10368279,
author={Park, Ji Hwan and Prasad, Vikash and Newsom, Sydney and Najar, Fares and Rajan, Rakhi},
journal={IEEE Computer Graphics and Applications},
title={idMotif: An Interactive Motif Identification in Protein Sequences},
year={2023},
volume={},
number={},
pages={1-13},
doi={10.1109/MCG.2023.3345742}}
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