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