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myanmar-ai-v3
amkyawdev/myanmar-ai-v3
myanmar-ai-v3 is a text generation model from amkyawdev. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Myanmar AI V3 သည် Qwen2.5-Coder-1.5B base model ပေါ်တွင် LoRA adapter ဖြင့် fine-tune လုပ်ထားသော မြန်မာဘာသာစကားအတွက် Language Model ဖြစ်ပါသည်။
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Public
Updated Jun 26, 2026
Repo size
85.3 MB
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Repo makeup
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Jun 26, 2026
- Updated
- Jun 26, 2026
- SHA
- a83ea5fb
Base models
Datasets
Model card
From the Hugging Face model README
🇲🇲 Myanmar AI V3
Myanmar AI V3 သည် Qwen2.5-Coder-1.5B base model ပေါ်တွင် LoRA adapter ဖြင့် fine-tune လုပ်ထားသော မြန်မာဘာသာစကားအတွက် Language Model ဖြစ်ပါသည်။
📋 Model Details
| Field | Details |
|---|---|
| Model Name | amkyawdev/myanmar-ai-v3 |
| Model Type | LoRA Adapter (Fine-tuned) |
| Base Model | Qwen/Qwen2.5-Coder-1.5B-Instruct |
| Language(s) | မြန်မာ (Burmese), English |
| License | MIT License |
| Developer | amkyawdev |
🔧 Technical Specifications
| Specification | Value |
|---|---|
| Architecture | Transformer-based Decoder (Causal LM) |
| Base Model Params | 1.5 Billion |
| LoRA Rank (r) | 16 |
| LoRA Alpha | 32 |
| LoRA Dropout | 0.05 |
| Target Modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
| Task Type | Causal Language Modeling |
🚀 Quick Start
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
MODEL_NAME = "amkyawdev/myanmar-ai-v3"
BASE_MODEL = "Qwen/Qwen2.5-Coder-1.5B-Instruct"
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
BASE_MODEL,
torch_dtype=torch.float16,
device_map="auto"
)
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, MODEL_NAME)
# Generate
text = "မြန်မာနိုင်ငံအကြောင်း ပြောပါ"
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
📊 Training Data
- Dataset: amkyawdev/myanmar-ai-training
- Data Format: SFT (Supervised Fine-Tuning) with system/user/assistant messages
⚠️ Limitations
- မြန်မာဘာသာစကားဖြင့် conversation ပြုလုပ်နိုင်ပါသည်
- English prompts များကိုလည်း နားလည်နိုင်ပါသည်
- Programming/code generation tasks များအတွက် အထူးသင့်တော်ပါသည် (Base model: Qwen2.5-Coder)
📞 Contact
Made with ❤️ for the Myanmar AI Community
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Languages
- my, en
- Created
- Jun 26, 2026
- Updated
- Jun 26, 2026