--- license: apache-2.0 language: - dv base_model: Qwen/Qwen3-8B tags: - dhivehi - maldives - thaana - qwen3 - lora - instruction-tuned library_name: transformers pipeline_tag: text-generation extra_gated_prompt: >- Access to Naturecode Dhivehi requires approval. This model is intended for research and development purposes for the Dhivehi language community. Please provide your intended use case for review. extra_gated_fields: Name: text Organization: text Country: text Use Case: text I agree to use this model responsibly: checkbox --- # Naturecode Dhivehi **The first production-ready Dhivehi language model for the Maldives.** Naturecode Dhivehi is a fine-tuned version of Qwen3-8B, trained specifically for the Dhivehi language (ދިވެހި) with comprehensive instruction-following capabilities. ## Model Details | Attribute | Value | |-----------|-------| | **Base Model** | Qwen/Qwen3-8B | | **Training Method** | CPT + SFT with LoRA | | **LoRA Rank** | 64 | | **LoRA Alpha** | 128 | | **Languages** | Dhivehi (ދިވެހި), English | ## Capabilities - **Formal Writing**: Letters, proposals, applications, official documents - **Informal Dhivehi**: Chat, social media, texting (romanized & Thaana) - **Creative Writing**: Stories, poems, songs, Boduberu lyrics - **Cultural Knowledge**: Maldivian traditions, customs, Islamic practices - **Translation**: English to Dhivehi bidirectional - **Q&A**: General knowledge about Maldives, geography, history - **Technical Writing**: Reports, documentation, explanations ## Important: System Prompt For best results, **always use this system prompt**: ``` ތިބާއަކީ ދިވެހި ބަހުގެ އެހީތެރިއެކެވެ. ކޮންމެ ޖަވާބެއްގައި މަދުވެގެން 5-8 ޖުމްލަ ހިމެނެން ވާނެއެވެ. ތަފްސީލީ، ފުރިހަމަ ޖަވާބުތައް ދެއްވާށެވެ. ``` Translation: "You are a Dhivehi language assistant. Each response should contain at least 5-8 sentences. Provide detailed, complete answers." ## Usage ### With ms-swift (Recommended) ```bash pip install ms-swift swift infer \ --model Qwen/Qwen3-8B \ --adapters naturecodeproject/dhivehi \ --stream true ``` ### With Transformers + PEFT ```python from transformers import AutoModelForCausalLM, AutoTokenizer from peft import PeftModel # Load base model base_model = AutoModelForCausalLM.from_pretrained( "Qwen/Qwen3-8B", torch_dtype="auto", device_map="auto" ) tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-8B") # Load adapter model = PeftModel.from_pretrained(base_model, "naturecodeproject/dhivehi") # System prompt system = "ތިބާއަކީ ދިވެހި ބަހުގެ އެހީތެރިއެކެވެ. ކޮންމެ ޖަވާބެއްގައި މަދުވެގެން 5-8 ޖުމްލަ ހިމެނެން ވާނެއެވެ. ތަފްސީލީ، ފުރިހަމަ ޖަވާބުތައް ދެއްވާށެވެ." messages = [ {"role": "system", "content": system}, {"role": "user", "content": "ދިވެހިރާއްޖޭގެ ވެރިރަށަކީ ކޮބާ؟"} ] text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) inputs = tokenizer(text, return_tensors="pt").to(model.device) outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.7) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` ## Example Output **Question:** ދިވެހިރާއްޖޭގެ ވެރިރަށަކީ ކޮބާ؟ **Response:** ދިވެހިރާއްޖޭގެ ވެރިރަށަކީ މާލެއެވެ. މާލެއަކީ ދިވެހިރާއްޖޭގެ އެންމެ ބޮޑު ސިޓީ އަދި ސިޔާސީ، އިޤްތިޞާދީ، ސަޤާފީ މަރުކަޒެވެ. މި ރަށުގައި ގާތްގަނޑަކަށް 200,000 އެއްހާ މީހުން ދިރިއުޅެއެވެ. މާލެއަކީ ދުނިޔޭގެ އެންމެ ތޮއްޖެހިފައިވާ ސިޓީތަކުގެ ތެރެއިން ސިޓީއެކެވެ. ## Maldives Knowledge | Fact | Value | |------|-------| | Capital | މާލެ (Malé) | | Islands | ~1,200 total, ~200 inhabited | | Population | ~500,000 | | Currency | Rufiyaa (ރުފިޔާ / MVR) | | Religion | Islam (100%) | | Language | Dhivehi (ދިވެހި) | | Independence | July 26, 1965 | ## Training Two-stage training approach: 1. **Continued Pretraining (CPT)**: Extended pretraining on Dhivehi text 2. **Supervised Fine-Tuning (SFT)**: Instruction tuning on curated Dhivehi data ## Limitations - Best performance with the recommended system prompt - May occasionally mix English words in responses - Knowledge cutoff applies to recent events ## Intended Use - Dhivehi language research and development - Building Dhivehi-language applications - Educational tools for the Maldivian community - Translation assistance ## License Apache 2.0 ## Citation ```bibtex @misc{naturecode-dhivehi, title={Naturecode Dhivehi: A Production-Ready Dhivehi Language Model}, author={Naturecode}, year={2024}, publisher={HuggingFace}, url={https://huggingface.co/naturecodeproject/dhivehi} } ``` --- **Built for the Maldives**