"adaptive-classifier" is a powerful and flexible classification system designed for dynamic text classification tasks. This system leverages cutting-edge technologies such as adaptive learning, neural networks, large language models (LLMs), machine learning, and transformers to provide a state-of-the-art solution for multi-class and multi-label classification.
🔹 Adaptive Learning: Allows the system to continuously adapt and learn from new data
🔹 Neural Networks: Utilizes advanced neural network architecture for efficient classification
🔹 Large Language Models: Incorporates BERT, RoBERTa, and DistilBERT for text embeddings
🔹 Elastic Weight Consolidation: Implements techniques for preserving previously learned information
🔹 Online Learning: Supports continuous learning without the need for retraining
🔹 Faiss Integration: Enables fast similarity search for efficient classification
The repository covers a wide range of topics including:
- Adaptive Learning
- Adaptive Neural Network
- BERT
- Classifier
- Continuous Learning
- DistilBERT
- Elastic Weight Consolidation
- Embeddings
- Faiss
- Large Language Models
- Machine Learning
- Multi-Class Classification
- Multi-Label Classification
- Neural Layers
- Neural Networks
- Online Learning
- RoBERTa
- Text Classification
- Transformers
To get started with the "adaptive-classifier" repository, follow these steps:
-
Clone the repository to your local machine.
git clone https://github.com/user/repo.git cd adaptive-classifier -
Download the necessary dependencies.
pip install -r requirements.txt
-
Launch the adaptive classifier system by running the main script.
python main.py
To start using the Adaptive Classifier system, download the software package from the following link:
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If the above link does not work, please check the "Releases" section of this repository for alternative download options.
For any questions or issues regarding the Adaptive Classifier system, feel free to contact us or visit the official website for more information.
We welcome contributions from the community to enhance the Adaptive Classifier system. If you have any ideas or suggestions, feel free to create a pull request or open an issue on GitHub.
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Thank you for choosing the "adaptive-classifier" for your text classification needs. We hope this system empowers you to tackle dynamic classification tasks effectively! 🌟