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gomi-sentiment
GitRatBCSAD/gomi-sentiment
gomi-sentiment is a text classification model from GitRatBCSAD. Use it when you need a label for a piece of text. The card lists the license as apache-2.0.
Fine-tuned DistilBERT (distilbert-base-uncased) for commit-message sentiment in the Gomi technical-debt risk pipeline.
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At a glance
- Task
- Text Classification
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- May 30, 2026
- Updated
- Oct 18, 2026
- SHA
- baefeb48
Try a prompt
Base models
Model card
From the Hugging Face model README
Gomi Sentiment Model
Fine-tuned DistilBERT (distilbert-base-uncased) for commit-message sentiment in the Gomi technical-debt risk pipeline.
Classifies short commit text into four labels:
| Label | Meaning | Risk signal in Gomi |
|---|---|---|
satisfaction | Positive / constructive tone | No |
neutral | Neutral tone | No |
caution | Hedging, workaround, “revisit later” | Yes |
frustration | Negative / stressed tone | Yes |
At runtime, Gomi aggregates per-file sentiment score as
(frustration + caution) / non–low-info commits.
Training
| Item | Detail |
|---|---|
| Base model | distilbert-base-uncased |
| Training data | GitRatBCSAD/gomi-datasets → openreview/openreview_labeled_2k.csv |
| Script | scripts/train_sentiment.py in the Gomi ML repo |
Prototype — Early checkpoint. Pin a revision tag (e.g.
v1.0.0) for reproducible runs.
Files in this repo
| File | Description |
|---|---|
config.json | Model config (4 labels) |
model.safetensors | Fine-tuned weights |
tokenizer.json | Tokenizer |
tokenizer_config.json | Tokenizer config |
Inference needs the files above. The checkpoints/ folder may be present from training uploads; it is not required at runtime.
Download
Hugging Face CLI
pip install huggingface_hub
huggingface-cli login # if private
hf download GitRatBCSAD/gomi-sentiment \
--local-dir ./distilbert_sentiment \
--revision v1.0.0
Python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
repo = "GitRatBCSAD/gomi-sentiment"
revision = "v1.0.0" # or None for main
tokenizer = AutoTokenizer.from_pretrained(repo, revision=revision)
model = AutoModelForSequenceClassification.from_pretrained(repo, revision=revision)
Git + LFS
git lfs install
git clone https://huggingface.co/GitRatBCSAD/gomi-sentiment
cd gomi-sentiment && git lfs pull
Use with Gomi
In the Gomi ML project .env:
GOMI_SENTIMENT_MODEL_REPO=GitRatBCSAD/gomi-sentiment
GOMI_SENTIMENT_MODEL_REVISION=v1.0.0
HF_TOKEN=your_token_if_private
Or download into scripts/datasets/distilbert_sentiment/ and run gomi.py without the env var.
Training data lives in gomi-datasets, not in this repo.
Related repos
| Repo | Role |
|---|---|
| gomi-datasets | CSV / JIT training data |
| gomi-risk | Logistic regression + SHAP background |
License
Apache 2.0. Respect licenses of distilbert-base-uncased and the OpenReview training data when redistributing.
- Task
- Text Classification
- Type
- distilbert
- License
- apache-2.0
- Created
- May 30, 2026
- Updated
- Oct 18, 2026