# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dev-analyzer/commit-message-model")
model = AutoModelForSequenceClassification.from_pretrained("dev-analyzer/commit-message-model")Quick Links
Model for classifying git commit messages. This model is based on vinai/bertweet-base and fine-tuned.
Git commit messages are categorized into the following categories:
- Adaptive - Adaptive activities are functional activities and involve making modifications to the software to ensure it remains compatible with new environments. Examples of these are feature additions and test cases.
- Perfective - Perfective activities encompass modifications aimed at improving the software's overall quality, structure, and efficiency, such as refactoring, renaming, cleaning up redundant segments, and improving algorithms and performance.
- Corrective - Corrective activities address and correct software problems such as bugs, defects, errors, and faults that negatively impact the system.
- Administrative - Administrative activities include working on documentation such as README.md files, javadocs, or commenting the code.
- Other - This activity includes Git operations such as merges and pull requests. It also includes vague and unspecified tasks.
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Model tree for dev-analyzer/commit-message-model
Base model
vinai/bertweet-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dev-analyzer/commit-message-model")