docs: add model card for OncoAgent v1.0 9B

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-9B
+tags:
+  - oncology
+  - medical
+  - lora
+  - peft
+  - qwen3
+  - amd
+  - rocm
+  - mi300x
+  - clinical
+  - fine-tuned
+datasets:
+  - MaximoLopezChenlo/OncoAgent-Clinical-266K
+language:
+  - en
+  - es
+pipeline_tag: text-generation
+library_name: peft
+---
+
+# 🧬 OncoAgent v1.0 — 9B (Tier 1)
+
+**QLoRA Fine-tuned LoRA Adapter for Clinical Oncology Triage**
+
+[![AMD](https://img.shields.io/badge/AMD-MI300X-ed1c24?logo=amd&logoColor=white)](https://www.amd.com/en/products/accelerators/instinct/mi300x.html)
+[![ROCm](https://img.shields.io/badge/ROCm-7.2-ed1c24)](https://rocm.docs.amd.com/)
+[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
+
+> **AMD Developer Hackathon 2026** · Trained on AMD Instinct™ MI300X · ROCm 7.2
+
+## Model Description
+
+OncoAgent v1.0 9B is a **QLoRA fine-tuned LoRA adapter** built on top of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B), specialized for **clinical oncology triage and treatment recommendation**.
+
+This is the **Tier 1 (fast triage)** model in the OncoAgent multi-agent system, optimized for:
+- Rapid cancer type classification and routing
+- Clinical entity extraction (symptoms, staging, biomarkers)
+- First-pass treatment recommendations based on NCCN/ESMO guidelines
+
+## Training Details
+
+| Parameter | Value |
+|---|---|
+| **Base Model** | Qwen/Qwen3.5-9B |
+| **Method** | QLoRA (4-bit NormalFloat4) |
+| **Framework** | Unsloth + PEFT + TRL |
+| **Hardware** | AMD Instinct™ MI300X (192GB HBM3) |
+| **Software** | ROCm 7.2 · PyTorch 2.3+ |
+| **LoRA Rank** | 32 |
+| **LoRA Alpha** | 32 |
+| **Target Modules** | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+| **Training Samples** | 240,168 (+ 26,686 eval) |
+| **Max Sequence Length** | 2,048 tokens |
+| **Batch Size** | 8 (gradient accumulation: 2 → effective: 16) |
+| **Learning Rate** | 2e-4 (cosine schedule) |
+| **Epochs** | 1 |
+| **Precision** | BF16 (native MI300X) |
+| **Seed** | 42 (reproducible) |
+
+## Dataset
+
+Trained on [MaximoLopezChenlo/OncoAgent-Clinical-266K](https://huggingface.co/datasets/MaximoLopezChenlo/OncoAgent-Clinical-266K), a curated oncology dataset combining:
+
+- **PMC-Patients** — Real clinical case presentations
+- **PubMedQA** — Evidence-based medical Q&A
+- **OncoCoT** — Chain-of-thought oncology reasoning (synthetic)
+- **NCCN/ESMO Guidelines** — Structured guideline extracts
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load base model
+base_model = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen3.5-9B",
+    device_map="auto",
+    torch_dtype="bfloat16",
+)
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.5-9B")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(
+    base_model,
+    "MaximoLopezChenlo/OncoAgent-v1.0-9B",
+)
+
+# Inference
+messages = [
+    {"role": "system", "content": "You are a clinical oncology specialist."},
+    {"role": "user", "content": "55yo female, Grade 1 endometrioid adenocarcinoma..."},
+]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
+outputs = model.generate(inputs, max_new_tokens=1024)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## vLLM Deployment (AMD MI300X)
+
+```bash
+# Serve with vLLM on ROCm
+python -m vllm.entrypoints.openai.api_server \
+    --model Qwen/Qwen3.5-9B \
+    --enable-lora \
+    --lora-modules oncoagent=MaximoLopezChenlo/OncoAgent-v1.0-9B \
+    --dtype bfloat16 \
+    --tensor-parallel-size 1 \
+    --gpu-memory-utilization 0.45
+```
+
+## Architecture
+
+OncoAgent v1.0 9B serves as the **Tier 1** model in a dual-tier architecture:
+
+```
+Clinical Case → Router → [Tier 1: 9B] → Specialist → Critic → Output
+                    ↓
+              (Complex cases)
+                    ↓
+              [Tier 2: 27B] → Specialist → Critic → Output
+```
+
+## Links
+
+- 🔗 **Demo:** [HF Space](https://huggingface.co/spaces/MaximoLopezChenlo/OncoAgent)
+- 🔗 **GitHub:** [maximolopezchenlo-lab/OncoAgent](https://github.com/maximolopezchenlo-lab/OncoAgent)
+- 🔗 **Tier 2 Model:** [OncoAgent-v1.0-27B](https://huggingface.co/MaximoLopezChenlo/OncoAgent-v1.0-27B)
+- 🔗 **Dataset:** [OncoAgent-Clinical-266K](https://huggingface.co/datasets/MaximoLopezChenlo/OncoAgent-Clinical-266K)
+
+## Citation
+
+```bibtex
+@misc{oncoagent2026,
+  title={OncoAgent: Multi-Agent Oncology Triage System},
+  author={Lopez Chenlo, Maximo},
+  year={2026},
+  howpublished={AMD Developer Hackathon 2026},
+  url={https://github.com/maximolopezchenlo-lab/OncoAgent}
+}
+```
+
+## License
+
+Apache 2.0 — This adapter is for **research and educational purposes only**. Not intended for direct clinical use without professional medical oversight.