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README.md

@@ -1,29 +1,51 @@
 ---
 license: apache-2.0
-datasets:
-- akemiH/NoteChat
-- starmpcc/Asclepius-Synthetic-Clinical-Notes
-- omi-health/medical-dialogue-to-soap-summary
-- openlifescienceai/medmcqa
-- GBaker/MedQA-USMLE-4-options
-- zhengyun21/PMC-Patients
 language:
-- en
-- ar
-metrics:
-- accuracy
-base_model:
-- google/medgemma-27b-text-it
-pipeline_tag: text-generation
+  - en
+  - ar
 tags:
-- Medical
-- Clinical-ai
-- MedGemma
-- Fine-Tuned
-- Diagnosis
-- Diff-Diagnosis
-- Clinical-transcription
-- Arabic-medical
+  - medical
+  - clinical-ai
+  - medgemma
+  - fine-tuned
+  - diagnosis
+  - differential-diagnosis
+  - clinical-transcription
+  - arabic-medical
+  - qlora
+  - healthcare
+  - gemma3_text
+base_model: google/medgemma-27b-text-it
+datasets:
+  - akemiH/NoteChat
+  - starmpcc/Asclepius-Synthetic-Clinical-Notes
+  - AGBonnet/augmented-clinical-notes
+  - omi-health/medical-dialogue-to-soap-summary
+  - openlifescienceai/medmcqa
+  - GBaker/MedQA-USMLE-4-options
+  - zhengyun21/PMC-Patients
+  - lingshu-medical-mllm/ReasonMed
+  - UCSC-VLAA/MedReason
+  - FreedomIntelligence/medical-o1-reasoning-SFT
+  - qiaojin/PubMedQA
+  - appier-ai-research/StreamBench
+  - MustafaIbrahim/medical-arabic-qa
+  - MKamil/arabic_medical_50k
+pipeline_tag: text-generation
+library_name: transformers
+model-index:
+  - name: Sanad-1.0
+    results:
+      - task:
+          type: text-generation
+          name: Medical Question Answering
+        dataset:
+          type: GBaker/MedQA-USMLE-4-options
+          name: MedQA USMLE
+        metrics:
+          - type: accuracy
+            value: 87.7
+            name: MedQA Accuracy
 ---
 
 # 🏥 Sanad-1.0 — Clinical AI Assistant