Text Classification
Transformers
PyTorch
gpt2
How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="codeparrot/codeparrot-small-complexity-prediction")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot-small-complexity-prediction")
model = AutoModelForSequenceClassification.from_pretrained("codeparrot/codeparrot-small-complexity-prediction")
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This is a fine-tuned version of codeparrot-small-multi, a 110M multilingual model for code generation, on CodeComplex, a dataset for complexity prediction of Java code.

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Dataset used to train codeparrot/codeparrot-small-complexity-prediction