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Upload BugFlow fine-tuned model

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README.md ADDED
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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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+ - severity-classification
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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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+
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+ # BugFlow Severity Classifier
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+
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+ Fine-tuned CodeBERT model for classifying bug report severity levels.
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+
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+ ## Labels
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+ - **Low**: Minor issues, cosmetic changes
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+ - **Medium**: Standard bugs affecting some functionality
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+ - **High**: Important bugs affecting major functionality
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+ - **Critical**: System crashes, data loss, security issues
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import RobertaTokenizer, RobertaForSequenceClassification
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+ import torch
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+
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+ model = RobertaForSequenceClassification.from_pretrained("YOUR_USERNAME/bugflow-severity-classifier")
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+ tokenizer = RobertaTokenizer.from_pretrained("YOUR_USERNAME/bugflow-severity-classifier")
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+
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+ text = "Application crashes when clicking login button"
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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 = ['low', 'medium', 'high', 'critical']
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+ predicted = labels[torch.argmax(probs).item()]
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+ print(f"Severity: {predicted}")
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+ ```
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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
config.json ADDED
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+ {
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+ "architectures": [
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+ "RobertaForSequenceClassification"
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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+ }
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+ }
merges.txt ADDED
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vocab.json ADDED
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vocab.txt ADDED
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