README.md

---
license: cc-by-nc-3.0
datasets:
- custom
language:
- en
base_model: google/gemma-2-9b-it
pipeline_tag: text-generation
library_name: peft
tags:
- nursing
- healthcare
- person-centred-care
- gemma2
- lora
- medical
---

# Relational Intelligence - Gemma 2 9B for Nursing

A fine-tuned Gemma 2 9B model specialised for **person-centred nursing care** and **relational practice**.

## Model Details

### Model Description

**Relational Intelligence** is a LoRA adapter fine-tuned on nursing care literature, designed to support nurses in understanding and applying person-centred care principles. Trained on open access journal articles from:

- **Foundation of Nursing Studies (FONS)** - [https://www.fons.org/](https://www.fons.org/)
- **International Practice Development Journal (IPDJ)** - ISSN: 2046-9292

This model respects the CC BY-NC 3.0 license of the source materials.
- **Developed by:** Nursing Citizen Development
- **Funded by:** Self-funded research project
- **Shared by:** NurseCitizenDeveloper
- **Model type:** LoRA Adapter (Causal Language Model)
- **Language(s) (NLP):** English
- **License:** [Creative Commons Attribution Non-Commercial 3.0](https://creativecommons.org/licenses/by-nc/3.0/)-
-  **Finetuned from model:** [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)

### Model Sources

- **Repository:** [NurseCitizenDeveloper/relational-intelligence-gemma2-9b](https://huggingface.co/NurseCitizenDeveloper/relational-intelligence-gemma2-9b)
- **Base Model:** [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)

## Uses

### Direct Use

- Educational support for nursing students and practitioners
- Care planning inspiration and person-centred approaches
- Reflective practice guidance and prompts
- Understanding nursing theoretical frameworks
- Research assistance in nursing literature

### Downstream Use

Can be integrated into:

- Clinical decision support tools
- Nursing education platforms
- Care planning applications
- Reflective practice journals

### Out-of-Scope Use

⚠️ **NOT for:**

- Clinical diagnosis
- Prescribing medications or treatments
- Emergency medical decisions
- Replacing professional clinical judgement
- Direct patient care without human oversight

## Bias, Risks, and Limitations

- **Not a diagnostic tool** - Cannot diagnose or recommend treatments
- **Knowledge limitations** - May not reflect latest evidence
- **Potential hallucinations** - May generate incorrect information
- **Cultural context** - Primarily trained on English Western nursing literature
- **No patient context** - Cannot examine patients

### Recommendations

- Always verify against current clinical guidelines
- Use as supportive tool, not replacement for expertise
- Never input identifiable patient information
- Follow your organisation's AI policies

## How to Get Started with the Model

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
    "google/gemma-2-9b-it",
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

# Load LoRA adapter
model = PeftModel.from_pretrained(
    base_model,
    "NurseCitizenDeveloper/relational-intelligence-gemma2-9b"
)

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")

# Generate
prompt = "<start_of_turn>user\nWhat are the key principles of person-centred care?<end_of_turn>\n<start_of_turn>model\n"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=500)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Training Details

### Training Data

- **Source:** FONS, IPDJ, person-centred care literature
- **Size:** 15,234 Q&A pairs
- **Topics:** Person-centred care, therapeutic relationships, reflective practice

### Training Procedure

#### Preprocessing

Q&A pairs generated from nursing literature using Gemini 2.5 Flash, formatted in Gemma chat template.

#### Training Hyperparameters

- **Training regime:** bf16 mixed precision, QLoRA (4-bit)
- **LoRA rank:** 64
- **LoRA alpha:** 16
- **Learning rate:** 2e-4
- **Batch size:** 1 (gradient accumulation: 4)
- **Epochs:** 3
- **Max sequence length:** 512
- **Optimizer:** paged_adamw_8bit

#### Speeds, Sizes, Times

- **Training time:** ~11 hours
- **Trainable parameters:** 216M (2.28%)
- **Total parameters:** 9.4B

## Environmental Impact

- **Hardware Type:** NVIDIA A100 GPU (40GB)
- **Hours used:** 11
- **Cloud Provider:** Google Colab
- **Compute Region:** US

## Technical Specifications

### Model Architecture and Objective

- **Architecture:** Gemma 2 9B decoder-only transformer
- **Adapter:** LoRA (Low-Rank Adaptation)
- **Objective:** Causal language modeling

### Compute Infrastructure

#### Hardware

NVIDIA A100 GPU, 40GB VRAM

#### Software

- `transformers >= 4.42.0`
- `peft >= 0.11.0`
- `trl >= 0.8.6`
- `bitsandbytes >= 0.43.0`

## Acknowledgments & Attribution

This model was trained on content from:

**Foundation of Nursing Studies (FONS)**
- Website: [https://www.fons.org/](https://www.fons.org/)
- The Foundation of Nursing Studies supports nurses and nursing to improve care

**International Practice Development Journal (IPDJ)**
- Website: [https://www.fons.org/library/journal/](https://www.fons.org/library/journal/)
- An open access journal published under CC BY-NC 3.0 license
- ISSN: 2046-9292

We gratefully acknowledge FONS for making nursing research openly accessible to support evidence-based practice and education.

### License Compliance

The training data derives from open access publications licensed under **Creative Commons Attribution Non-Commercial 3.0 (CC BY-NC 3.0)**.

Accordingly, this model and its outputs:
- ✅ May be used for educational purposes
- ✅ May be used for research
- ✅ May be adapted with attribution
- ❌ May NOT be used for commercial purposes

## Citation

**BibTeX:**

```bibtex
@misc{relational-intelligence-2025,
  author = {Lincoln Gombedza},
  title = {Relational Intelligence: A Fine-Tuned Gemma 2 Model for Nursing},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/NurseCitizenDeveloper/relational-intelligence-gemma2-9b}
}
```

**APA:**

Lincoln Gombedza. (2025). *Relational Intelligence: A Fine-Tuned Gemma 2 Model for Nursing*. Hugging Face. https://huggingface.co/NurseCitizenDeveloper/relational-intelligence-gemma2-9b

## Model Card Authors

Lincoln Gombedza 

## Model Card Contact

- **HuggingFace:** [@NurseCitizenDeveloper](https://huggingface.co/NurseCitizenDeveloper)
- **Email:** [info@nursingcitizendevelopment.com](mailto:info@nursingcitizendevelopment.com)