# Model Name This repository hosts a fine-tuned machine learning model uploaded on Hugging Face for research and educational purposes. --- ## π Model Overview - **Base Model:** Qwen/Qwen3-4B-Instruct - **Task:** Text Classification - **Framework:** Transformers (PyTorch) - **License:** Apache 2.0 This model is designed to analyze input text and perform classification tasks useful for intelligent agents and AI-based applications. --- ## π― Intended Use - Text classification - AI agent decision-making - Academic research - Educational demonstrations --- ## π« Limitations - The model may not generalize well to unseen domains. - It should not be used for high-risk or sensitive applications without additional evaluation. --- ## π Evaluation Results This model has not been formally evaluated yet. Evaluation metrics will be added in a future version. --- ## π§ Training Data The model was trained using a **custom dataset** prepared specifically for the intended task. --- ## βοΈ Ethical Considerations Users should ensure responsible usage and avoid misuse of the model. Biases may exist depending on the training data. --- ## π¦ How to Use ```python from transformers import pipeline classifier = pipeline("text-classification", model="your-username/model-name") result = classifier("Your input text here") print(result)
Model Overview
Base Model: Qwen/Qwen3-4B-Instruct
Task: Text Classification
Framework: Transformers (PyTorch)
License: Apache 2.0
This model is designed to analyze input text and perform classification tasks useful for intelligent agents and AI-based applications.
π― Intended Use
Text classification
AI agent decision-making
Academic research
Educational demonstrations
π« Limitations
The model may not generalize well to unseen domains.
It should not be used for high-risk or sensitive applications without additional evaluation.
π Evaluation Results
This model has not been formally evaluated yet.
Evaluation metrics will be added in a future version.
π§ Training Data
The model was trained using a custom dataset prepared specifically for the intended task.
βοΈ Ethical Considerations
Users should ensure responsible usage and avoid misuse of the model.
Biases may exist depending on the training data.
Add initial README and model card