
# ONNX version of huggingface/CodeBERTa-language-id

**This model is conversion of [huggingface/CodeBERTa-language-id](https://huggingface.co/huggingface/CodeBERTa-language-id) to ONNX.** The model was converted to ONNX using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) 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](https://huggingface.co/docs/optimum/index) library installed.

```python
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
"""))
```

### LLM Guard

[Code scanner](https://llm-guard.com/input_scanners/code/)

## Community

Join our Slack to give us feedback, connect with the maintainers and fellow users, ask questions, 
or engage in discussions about LLM security!

<a href="https://join.slack.com/t/laiyerai/shared_invite/zt-28jv3ci39-sVxXrLs3rQdaN3mIl9IT~w"><img src="https://github.com/laiyer-ai/llm-guard/blob/main/docs/assets/join-our-slack-community.png?raw=true" width="200"></a>

{"language": ["code"], "tags": ["code", "programming-language"], "datasets": ["code_search_net"], "pipeline_tag": "text-classification", "inference": false}
transformers onnx roberta text-classification code programming-language dataset:code_search_net autotrain_compatible region:us