Text Classification
Transformers
Safetensors
roberta
quantum-computing
quantum-software-engineering
code-classification
codebert
c2q
Instructions to use boshuai1/c2q-parser-codebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boshuai1/c2q-parser-codebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boshuai1/c2q-parser-codebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boshuai1/c2q-parser-codebert") model = AutoModelForSequenceClassification.from_pretrained("boshuai1/c2q-parser-codebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: text-classification | |
| tags: | |
| - quantum-computing | |
| - quantum-software-engineering | |
| - code-classification | |
| - codebert | |
| - c2q | |
| # C2|Q> Parser Model | |
| This repository contains the released parser model checkpoint for the paper: | |
| **C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development** | |
| arXiv: [2510.02854](https://arxiv.org/abs/2510.02854) | |
| TOSEM 2026 | |
| DOI: [10.1145/3803018](https://doi.org/10.1145/3803018) | |
| ## Purpose | |
| This model is the released inference checkpoint used in the C2|Q> framework to classify supported problem families from classical Python code inputs. | |
| It is part of the encoder stage of the framework and supports the Python-code route of the artifact. | |
| ## Source Project | |
| - GitHub: [C2-Q/C2Q](https://github.com/C2-Q/C2Q) | |
| - Paper (arXiv): [2510.02854](https://arxiv.org/abs/2510.02854) | |
| - Paper (TOSEM): [10.1145/3803018](https://doi.org/10.1145/3803018) | |
| ## Archival Record | |
| The archival copy of this model is preserved on Zenodo: | |
| - Zenodo DOI: [10.5281/zenodo.19061126](https://doi.org/10.5281/zenodo.19061126) | |
| Hugging Face is provided for discoverability and easier community access. Zenodo remains the archival source. | |
| ## Files | |
| This repository contains a released model checkpoint compatible with the `transformers` ecosystem, including configuration, tokenizer files, and model weights. | |
| ## Intended Use | |
| - artifact inspection | |
| - local inference | |
| - parser-backed execution in C2|Q> | |
| ## Limitations | |
| - this is a released checkpoint, not a full retraining package | |
| - full parser training provenance remains in the project repository and associated artifact materials | |
| - current artifact support is documented around Python 3.12 | |
| ## License | |
| Apache-2.0 | |