from transformers import pipeline

classifier = pipeline("text-classification", model="sankalp-indish/alexithymia-adhd-predictor")
classifier("I often find it hard to describe how I feel.")

📈 Example Output

The model takes in short user inputs and returns a probabilistic score for both Alexithymia and ADHD traits.

Input Text	Alexithymia Score	ADHD Score
"I often struggle to explain what I'm feeling."	1	0
"I get distracted easily and can't finish tasks on time."	0	1
"Sometimes I can't tell if I'm anxious or excited."	1	0
"I daydream a lot and forget what I'm doing."	0	1

🧪 These values are probabilities, not diagnoses. Scores above 0.5 and 0.3 (based on the availability of the dataset) suggest strong presence of that trait.

🧠 Behind the Model

This classifier is trained on combined NLP embeddings from real-world psychological scale responses. It uses probabilistic classification to predict traits, not diagnoses. And currently is scale and input of text based
Framework: bertopic + sklearn
Fine-tuned over custom-labeled dataset
Designed for interpretability & simplicity

⚠️ Disclaimer

This tool is not a substitute for clinical diagnosis. It is provided for research and educational use only. Please consult a qualified mental health professional for clinical assessment.

👨‍💻 Author

Developed by Sankalp Indish [sankalp_indish] https://huggingface.co/sankalp-indish