# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("notaphoenix/shakespeare_classifier_model")
model = AutoModelForSequenceClassification.from_pretrained("notaphoenix/shakespeare_classifier_model")Quick Links
Shakespeare/Modern English DistilBert-base
Description ℹ
With this model, you can classify if an English sentence has a Shakespearean style or a modern style
The model is a fine-tuned checkpoint of DistilBERT-base-uncased.
Application 🚀
Return all labels
from transformers import pipeline
classifier = pipeline("text-classification", model="notaphoenix/shakespeare_classifier_model", top_k=None)
classifier("This is a modern sentence!")
[[
{'label': 'modern', 'score': 0.901931643486023},
{'label': 'shakespearean', 'score': 0.09806833416223526}
]]
Return top label
from transformers import pipeline
classifier = pipeline("text-classification", model="notaphoenix/shakespeare_classifier_model")
classifier("This is a modern sentence!")
[
{'label': 'modern', 'score': 0.901931643486023}
]
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="notaphoenix/shakespeare_classifier_model")