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---
language: multilingual
tags:
- adaptive-classifier
- text-classification
- continuous-learning
license: apache-2.0
---
# Adaptive Classifier
This model is an instance of an [adaptive-classifier](https://github.com/codelion/adaptive-classifier) that allows for continuous learning and dynamic class addition.
You can install it with `pip install adaptive-classifier`.
## Model Details
- Base Model: BAAI/bge-small-en-v1.5
- Number of Classes: 3
- Total Examples: 3
- Embedding Dimension: 384
## Class Distribution
```
negative: 1 examples (33.3%)
neutral: 1 examples (33.3%)
positive: 1 examples (33.3%)
```
## Usage
```python
from adaptive_classifier import AdaptiveClassifier
# Load the model
classifier = AdaptiveClassifier.from_pretrained("adaptive-classifier/model-name")
# Make predictions
text = "Your text here"
predictions = classifier.predict(text)
print(predictions) # List of (label, confidence) tuples
# Add new examples
texts = ["Example 1", "Example 2"]
labels = ["class1", "class2"]
classifier.add_examples(texts, labels)
```
## Training Details
- Training Steps: 1
- Examples per Class: See distribution above
- Prototype Memory: Active
- Neural Adaptation: Active
## Limitations
This model:
- Requires at least 3 examples per class
- Has a maximum of 1000 examples per class
- Updates prototypes every 100 examples
## Citation
```bibtex
@software{adaptive_classifier,
title = {Adaptive Classifier: Dynamic Text Classification with Continuous Learning},
author = {Sharma, Asankhaya},
year = {2025},
publisher = {GitHub},
url = {https://github.com/codelion/adaptive-classifier}
}
```
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