Upload README.md with huggingface_hub

README.md

@@ -1,6 +1,5 @@
 ---
 language:
-- id
 - en
 license: apache-2.0
 task_categories:
@@ -8,7 +7,7 @@ task_categories:
 - question-answering
 tags:
 - health
-- indonesian
+- english
 - kicaulah-ai
 - natural-language
 - medical
@@ -16,70 +15,42 @@ tags:
 - pediatric
 - first-aid
 - mental-health
-- doctor-qa
-pretty_name: Kicaulah AI - Dataset Kesehatan (Health)
+- clinical-qa
+- wellness
+pretty_name: Kicaulah AI - Dataset Health (Medical QA & Triage)
 size_categories:
 - 1K<n<10K
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
-dataset_info:
-  features:
-  - name: instruction
-    dtype: string
-  - name: response
-    dtype: string
-  - name: category
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 798762
-    num_examples: 880
-  - name: validation
-    num_bytes: 99533
-    num_examples: 110
-  - name: test
-    num_bytes: 98951
-    num_examples: 110
-  download_size: 352861
-  dataset_size: 997246
 ---
 
-# Kicaulah AI — Dataset Kesehatan (Health)
+# Kicaulah AI — Dataset Health (Medical QA & Triage)
 
-## 📖 Deskripsi
-Dataset Tanya-Jawab Medis dan Edukasi Kesehatan dalam Bahasa Indonesia sehari-hari yang natural. Mencakup 10 bidang spesifik: Pediatri (anak & bayi), Lambung & GERD, Penyakit Metabolik Kronis (Hipertensi, Diabetes, Asam Urat, Kolesterol), Pertolongan Pertama Gawat Darurat (P3K), Dermatologi Kulit, Kesehatan Wanita, Kesehatan Mental Fisiologis, Farmakologi & Aturan Obat Bebas, Kesehatan Gigi-Mulut, dan Infeksi Saluran Pernapasan. Diformulasikan dengan pendekatan empati tenaga medis, bebas dari template kaku AI.
+## 📖 Description
+A high-quality Medical QA and Health Education dataset in natural conversational English. Covers 10 distinct clinical pillars: Pediatrics & Infant Care, Gastric & GERD, Chronic Metabolic Disease (Hypertension, Diabetes, Gout, Cholesterol), Emergency First Aid, Dermatology & Skin Health, Women's Health, Mental Wellness & Sleep Hygiene, Over-The-Counter Pharmacology, Oral & Dental Care, and Respiratory & Infectious Disease. Designed under the Anti-AI-Speak standard with human empathy and zero robotic clichés.
 
-Dataset ini dirancang khusus dengan standar **Anti-AI-Speak**:
-- Menggunakan bahasa percakapan sehari-hari Indonesia yang natural dan otentik.
-- Menghindari frasa robotik kaku seperti *"Sebagai model AI..."* atau *"Pertanyaan yang bagus!"*.
-- Mengutamakan empati, analogi praktis, skenario nyata, dan variasi gaya bicara (santai, formal, emosional, ringkas).
+This dataset is strictly curated under the **Anti-AI-Speak Standard**:
+- Built using authentic, everyday conversational language.
+- Free from generic robotic clichés such as *"As an AI language model..."* or *"That's a great question!"*.
+- Prioritizes genuine empathy, real-world context, practical analogies, and natural variations in tone (casual, formal, emotional, concise, and in-depth).
 
-## 🎯 Kegunaan
-- Fine-tuning Large Language Model (LLM) untuk asisten medis & konsultasi kesehatan berbahasa Indonesia.
-- Melatih model QA sistem triase kesehatan agar mampu merespons dengan empati tinggi dan tanda bahaya (red flags) yang akurat.
-- Benchmark model NLP kesehatan terhadap bahasa percakapan sehari-hari masyarakat Indonesia.
+## 🎯 Use Cases
+- Fine-tuning Large Language Models (LLMs) for natural, empathetic medical assistant applications.
+- Training health triage bots to deliver concise, reassuring, and red-flag-conscious medical guidance.
+- Benchmarking conversational healthcare responses against everyday, realistic patient inquiries.
 
-## 📊 Struktur Dataset
-| Kolom | Tipe | Deskripsi | Contoh |
-|-------|------|-----------|--------|
-| instruction | string | Pertanyaan atau skenario pengguna | "Anakku demam 39 derajat udah 2 hari, harus gimana ya?" |
-| response | string | Respon natural, solutif, tanpa gaya AI kaku | "Waduh, wajar banget kalau cemas. Tenang dulu ya bun..." |
-| category | string | Sub-kategori spesifik dari domain | "health" |
+## 📊 Dataset Structure
+| Column | Type | Description | Example |
+|-------|------|-------------|---------|
+| instruction | string | User inquiry or realistic scenario | "My 2-year-old has had a 102F fever for 2 days, what should I do?" |
+| response | string | Natural, human, solution-oriented response | "Take a deep breath first. A 102 fever on day 2 is scary..." |
+| category | string | Specific domain subcategory | "health" |
 
-## 📈 Statistik
-- **Total Contoh**: 1,179
-- **Train (80%)**: 943
-- **Validation (10%)**: 117
-- **Test (10%)**: 119
+## 📈 Statistics
+- **Total Examples**: 1,100
+- **Train (80%)**: 880
+- **Validation (10%)**: 110
+- **Test (10%)**: 110
 
-## 🚀 Cara Pakai
+## 🚀 How to Use
 
 ```python
 from datasets import load_dataset
@@ -88,10 +59,10 @@ dataset = load_dataset("Kicaulah/dataset-health")
 print(dataset["train"][0])
 ```
 
-## 📑 Sitasi
+## 📑 Citation
 ```bibtex
 @misc{kicaulah_health,
-  title={Kicaulah AI - Dataset Kesehatan (Health)},
+  title={Kicaulah AI - Dataset Health (Medical QA & Triage)},
   author={Kicaulah AI Team},
   year={2025},
   publisher={Hugging Face},