Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs
Paper ⢠2502.12982 ⢠Published ⢠19
Min Si Thu
jojo-ai-mst
AI & ML interests
Computer Vision
NLP
Audio
Recent Activity
posted an update 15 days ago
đ˛đ˛ Releasing the Myanmar Tuberculosis Instruction Dataset â a MyanmarâEnglish parallel corpus for medical NLP in one of the lowest-resourced language settings in Southeast Asia.
Most TB datasets are either structured clinical data or English-only research corpora. This one fills a different gap: instructional, guideline-based content in Burmese, formatted for instruction tuning and medical QA.
### What's inside
- 2,043 instructionâresponse pairs
- MyanmarâEnglish parallel
- 7 TB domains: treatment, diagnostics, drug management, MDR-TB, infection control, patient education, healthcare worker training
- Sourced from WHO guidelines, Myanmar NTP protocols, and standard medical references
- MIT licensed
Useful for
- Fine-tuning Myanmar-language medical LLMs
- TB question answering
- Translation evaluation in a medical domain
- General low-resource medical NLP
```
from datasets import load_dataset
ds = load_dataset("jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions")
```
đ https://huggingface.co/datasets/jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions
Built by Min Si Thu and Khin Myat Noe. Feedback welcome â especially from anyone working on SEA medical AI or Burmese NLP.
#MedicalAI #LowResourceNLP #Myanmar #Burmese #Tuberculosis #InstructionTuning
updated a collection 15 days ago
Burmese Language Datasets updated a dataset 15 days ago
jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-InstructionsOrganizations
authored a
paper about 1 year ago