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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- quantumindssi
+- sovereign-ai
+- edge-computing
+- healthcare-medical-ai
+- drug-interactions
+- pharmacovigilance
+- ddi
+- patient-safety
+- 09_drug_interaction_predictor
+- finetuned
+- lora
+inference: true
+---
+
+# Drug Interaction Predictor
+
+A fine-tuned Small Language Model (SLM) that predicts potential drug-drug interactions from medication lists, including severity, mechanism, evidence, and clinical recommendations.
+
+## Model Details
+
+| Attribute | Value |
+|-----------|-------|
+| **Developer** | QuantumIndSSI Ltd |
+| **Base Model** | ./base_model |
+| **Architecture** | Transformer decoder (causal LM) |
+| **Fine-tuning Method** | LoRA (Low-Rank Adaptation) |
+| **LoRA Rank** | 16 |
+| **LoRA Alpha** | 32 |
+| **License** | apache-2.0 |
+
+## Intended Use
+
+- Automated drug-drug interaction screening from medication lists
+- Clinical decision support for pharmacists and prescribers
+- Patient safety and pharmacovigilance workflows
+- Edge deployment on Victron and other constrained hardware
+
+## Training Data
+
+- 100,000+ synthetic drug-drug interaction examples
+- Drug classes: anticoagulants, statins, antibiotics, antidepressants, PPIs, NSAIDs, opioids, immunosuppressants, and more
+- Interaction types: pharmacokinetic (CYP inhibition/induction, P-gp), pharmacodynamic (additive toxicity, QT prolongation, bleeding)
+- Severity levels: Critical, High, Medium, Low
+
+## Usage
+
+```python
+model_id = "QuantumindSSI/09_drug_interaction_predictor"
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model = AutoModelForCausalLM.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+prompt = """Medications: Warfarin, Aspirin, Omeprazole. Analyze for interactions."""
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Limitations
+
+- Not a substitute for clinical pharmacologist review
+- Synthetic training data may not capture all real-world interactions
+- English only
+- Always verify with FDA labels, clinical guidelines, and drug databases
+
+## Hardware Requirements
+
+| Target | RAM | Notes |
+|--------|-----|-------|
+| Cloud GPU | 4GB | FP16 inference |
+| Workstation | 3GB | INT8 quantized |
+| Victron Edge | 2-3GB | INT8/INT4 quantized, CPU |
+
+## Citation
+
+```bibtex
+@misc{09_drug_interaction_predictor,
+  title={Drug Interaction Predictor},
+  author={QuantumIndSSI Ltd},
+  year={2026},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/QuantumindSSI/09_drug_interaction_predictor}}
+}
+```
+
+## Contact
+
+- GitHub: https://github.com/QuantumindSSI
+- HuggingFace: https://huggingface.co/QuantumindSSI

adapter_config.json

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+  "alpha_pattern": {},
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+  "auto_mapping": null,
+  "base_model_name_or_path": "./base_model",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
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+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
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+  "loftq_config": {},
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+  "lora_bias": false,
+  "lora_dropout": 0.05,
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+  "megatron_config": null,
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+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
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+    "o_proj",
+    "gate_proj",
+    "q_proj",
+    "down_proj",
+    "v_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful assistant.<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

tokenizer.json

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tokenizer_config.json

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+  "pad_token": "<|endoftext|>",
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+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

training_args.bin

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