metadata

datasets:
  - code_search_net
language:
  - code
pipeline_tag: text-classification
inference: false
tags:
  - code
  - programming-language
base_model: huggingface/CodeBERTa-language-id

ONNX version of huggingface/CodeBERTa-language-id

This model is conversion of huggingface/CodeBERTa-language-id to ONNX. The model was converted to ONNX using the 🤗 Optimum library.

Model Architecture

Base Model: CodeBERTa, a variant of the RoBERTa model trained specifically for programming languages.

Modifications: No changes except for the conversion.

Usage

Optimum

Loading the model requires the 🤗 Optimum library installed.

from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import AutoTokenizer, pipeline


tokenizer = AutoTokenizer.from_pretrained("laiyer/CodeBERTa-language-id")
model = ORTModelForSequenceClassification.from_pretrained("laiyer/CodeBERTa-language-id")
classifier = pipeline(
    task="text-classification",
    model=model,
    tokenizer=tokenizer,
)

print(classifier("""
def f(x):
    return x**2
"""))

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