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--- |
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language: en |
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tags: |
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- bug-classification |
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- team-assignment |
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- software-engineering |
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license: apache-2.0 |
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datasets: |
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- custom-github-issues |
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pipeline_tag: text-classification |
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--- |
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# BugFlow Team Classifier |
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Fine-tuned CodeBERT model for assigning bugs to the appropriate development team. |
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## Labels |
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- **Frontend**: UI, CSS, layout, display issues |
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- **Backend**: API, server, database, logic issues |
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- **Mobile**: iOS, Android, mobile app issues |
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- **DevOps**: Deployment, CI/CD, infrastructure issues |
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## Usage |
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```python |
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from transformers import RobertaTokenizer, RobertaForSequenceClassification |
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import torch |
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model = RobertaForSequenceClassification.from_pretrained("YOUR_USERNAME/bugflow-team-classifier") |
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tokenizer = RobertaTokenizer.from_pretrained("YOUR_USERNAME/bugflow-team-classifier") |
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text = "Button not responding on click" |
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inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True) |
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outputs = model(**inputs) |
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probs = torch.softmax(outputs.logits, dim=1) |
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labels = ['Backend', 'Frontend', 'Mobile', 'DevOps'] |
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predicted = labels[torch.argmax(probs).item()] |
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print(f"Team: {predicted}") |
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``` |
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## Training |
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- Base model: microsoft/codebert-base |
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- Dataset: Custom GitHub issues dataset + domain-specific bugs |
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- Fine-tuned using Hugging Face Transformers |
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