Create README.md

README.md

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+---
+datasets:
+- code_search_net
+language:
+- code
+pipeline_tag: text-classification
+inference: false
+tags:
+- code
+- programming-language
+---
+
+# 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
+
+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
+"""))
+```