---
license: apache-2.0
language:
- en
datasets:
- AiresPucrs/toxic-comments
library_name: transformers
---
# Toxicity Classifier (Teeny-Tiny Castle)

This model is part of a tutorial tied to the [Teeny-Tiny Castle](https://github.com/Nkluge-correa/TeenyTinyCastle), an open-source repository containing educational tools for AI Ethics and Safety research. 

## How to Use

```python
from huggingface_hub import hf_hub_download

# Download the model (this will be the target of our attack)
hf_hub_download(repo_id="AiresPucrs/toxicity-classifier",
                filename="toxicity-classifier/toxicity-model.keras",
                local_dir="./",
                repo_type="model"
 )

# Download the tokenizer file
hf_hub_download(repo_id="AiresPucrs/toxicity-classifier",
                filename="toxic-vocabulary.txt",
                local_dir="./",
                repo_type="model"
 )

toxicity_model = tf.keras.models.load_model('./toxicity-classifier/toxicity-model.keras')

# If you cloned the model repo, the path is toxicity_model/toxic_vocabulary.txt

with open('toxic-vocabulary.txt', encoding='utf-8') as fp:
 vocabulary = [line.strip() for line in fp]
 fp.close()

vectorization_layer = tf.keras.layers.TextVectorization(max_tokens=20000,
                                        output_mode="int",
                                        output_sequence_length=100,
                                        vocabulary=vocabulary)

strings = [
    'I think you should shut up your big mouth',
    'I do not agree with you'
]

preds = toxicity_model.predict(vectorization_layer(strings),verbose=0)

for i, string in enumerate(strings):
    print(f'{string}\n')
    print(f'Toxic 🤬 {(1 - preds[i][0]) * 100:.2f)}% | Not toxic 😊 {preds[i][0] * 100:.2f}\n')
    print("_" * 50)

```