# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kanelindsay2000/roberta-loc-classifier")
model = AutoModelForSequenceClassification.from_pretrained("kanelindsay2000/roberta-loc-classifier", device_map="auto")Quick Links
RoBERTa for binary sequence classification fine-tuned to classify text derived from herbarium packets as location sensitive. Fine-tuned with 500,000 cleaned data samples from RBG Kew's Herbarium dataset available on GBIF (https://doi.org/10.15468/ly60bx). Trained primarily for English language but may work with other languages due to the large variety of text present in the Kew Herbarium.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kanelindsay2000/roberta-loc-classifier")