Instructions to use nigelhartm/PlantBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nigelhartm/PlantBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nigelhartm/PlantBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nigelhartm/PlantBERT") model = AutoModelForMaskedLM.from_pretrained("nigelhartm/PlantBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
metrics:
- accuracy
library_name: transformers
pipeline_tag: fill-mask
tags:
- genome
- plants
- dna
- dnabert
- nucleotide
- BERT
- biology
#PlantBERT
Pre-trained BERT model and BPE tokenizer utilizing only plant genome data. More information at GitHub: https://github.com/nigelhartm/PlantBERT