transformers tf safetensors distilbert text-classification generated_from_keras_callback autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_keras_callback
model-index:
- name: distilbert-base-cased-sentiment-classifier
  results: []
---
# DistilBERT Sentiment 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 transformers import TFAutoModelForSequenceClassification, AutoTokenizer
from transformers import TextClassificationPipeline

# Load the model and tokenizer
model = TFAutoModelForSequenceClassification.from_pretrained("AiresPucrs/distilbert-base-cased-sentiment-classifier")
tokenizer = AutoTokenizer.from_pretrained("AiresPucrs/distilbert-base-cased-sentiment-classifier")

# Create a text classification pipeline
pipeline = TextClassificationPipeline(model=model, tokenizer=tokenizer)

# Classify some samples
texts = [
    'Is to complicated and boring.',
    'Is nice to see philosophers doing machine learning.',
 ]

for text in texts:
 preds = pipeline(text)

  print(f"""\nReview: '{text}'\n(Label: {preds[0]['label']} | Confidence: {preds[0]['score'] * 100:.2f}%)""")
```