from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="akaruineko/ftan-2.0"
)

result = classifier("you are stupid")
print(result)

Example:

[{'label': 'offensive', 'score': 0.965}]

Intended Use

ftan-2.0 can be used for:

content moderation
filtering offensive messages
dataset preprocessing
text classification experiments
moderation pipelines
research and experimentation with text classifiers

Limitations

This model should not be treated as a perfect moderation system.

Offensiveness can depend heavily on context, intent, quotation, sarcasm, reclaimed language, and the surrounding conversation. The model may therefore produce incorrect predictions for ambiguous or context-dependent text.

For example, a sentence discussing an offensive word may still receive a non-trivial offensive score even when the sentence itself is not an insult.

The model also operates on individual text inputs and does not have access to conversation history unless it is explicitly provided as input.

Example Predictions

Some example inference results:

text

"b****" # censored
→ offensive (0.988)

"you are stupid"
→ offensive (0.965)

"the word \"stupid\" is offensive"
→ offensive (0.695)

"beach"
→ clean (0.922)

These examples are illustrative and should not be interpreted as a formal benchmark.

License

See the repository/model files for the applicable license.

Author

Created by akaruineko.

This model is the 2.0 continuation of the bad-good-classifier-ru_en project.