--- license: llama3 language: - en library_name: peft base_model: meta-llama/Meta-Llama-3-8B pipeline_tag: text-generation tags: - peft - lora - llama-3 - tabular-data - adolescent-mental-health ---

MindScale

A Psychometric Foundation Model for
Population-Scale Adolescent Mental Health Assessment

Overview · Training · Loading · Use · Limitations · License

## 📋 Overview - **Model** MindScale is a language-model-based psychometric foundation model adapted from [Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) for questionnaire-based adolescent mental health screening and psychiatric symptom assessment. - **Released files** The release contains LoRA adapter weights and requires the base model for use.

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## 📊 Training Details - **Dataset**: Large-scale adolescent questionnaire dataset - **Scale**: 402,301 students from 377 schools - **Instruments**: 22 questionnaires comprising 250 items - **Information domains**: Environmental factors, psychological characteristics, and questionnaire-derived psychiatric symptoms - **Training method**: LoRA-based parameter-efficient fine-tuning - **Training stages**: Pretraining, at-risk identification, and psychiatric symptom assessment - **Data access**: The full participant-level training cohort is not included because it contains sensitive information from adolescents.

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## 🤗 Loading the Adapters - **Adapter directories**: `Pretrain/`, `Screen/`, and `Assessment/`. - **Stage dependencies**: Screening requires the pretraining and screening adapters; assessment requires all three. - **Before running**: Use the MindScale code directory with its runtime dependencies installed. The example uses the code release's helpers to prepare special tokens and stage adapters consistently. ```python from pathlib import Path from huggingface_hub import snapshot_download from transformers import AutoTokenizer from configs import ( SerializerConfig, TokenizerConfig, TrainConfig_Screen, LoraConfig_Screen, ) from models.llama_model import load_llama_3_lora base_model_id = "meta-llama/Meta-Llama-3-8B" adapter_id = "Rango001/Adolescent-mental-health" weights_dir = Path(snapshot_download( repo_id=adapter_id, allow_patterns=["*/adapter_config.json", "*/adapter_model.safetensors"], )) tokenizer = AutoTokenizer.from_pretrained(base_model_id, use_fast=False) model, tokenizer = load_llama_3_lora( tokenizer, SerializerConfig(), TokenizerConfig(), base_model_id, task_type="Screen", train_config=TrainConfig_Screen(), lora_config=LoraConfig_Screen(), pretrain_state_dict_path=str(weights_dir / "Pretrain"), screen_state_dict_path=str(weights_dir / "Screen"), test_task=True, ) model.eval() ``` - **Base model access**: Accept the Meta Llama 3 license on Hugging Face. - **Runtime**: A CUDA-enabled environment is required. The example uses the code release's existing 8-bit loading. - **Questionnaire inference**: Follow the accompanying code README for input preparation and prediction export.

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## 📝 Intended Use MindScale is intended for: - **Population screening**: Research on adolescent mental health assessment. - **Method development**: Studies of structured questionnaire modelling. - **Model evaluation**: Evaluation on questionnaire-derived tabular data.

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## ⚠️ Limitations - **Input scope**: The model was trained on questionnaire-based data and may not generalize to other input formats or populations. - **Class imbalance and bias**: Predictions may be affected by class imbalance and cohort-specific biases. - **Clinical validation**: The model has not been validated for routine clinical use. - **Distribution shifts**: Performance may decline under demographic, linguistic, institutional, or other distribution shifts.

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## 🛡️ Ethical Considerations - **Research use only**: MindScale must not be used for clinical diagnosis, treatment decisions, crisis triage, or autonomous decisions affecting students. - **Prediction uncertainty**: Outputs may be incorrect or biased, particularly for underrepresented groups. - **Participant protection**: Any use involving participant data requires appropriate ethical approval, privacy protection, fairness assessment, and qualified human oversight.

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## 📄 License Use of this adapter and the Meta-Llama-3-8B backbone is subject to the [Meta Llama 3 Community License](https://llama.meta.com/llama3/license/) and its Acceptable Use Policy.

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