metadata
license: apache-2.0
language:
- dv
base_model: google/functiongemma-270m-it
tags:
- dhivehi
- maldives
- conversational
- naturecode
library_name: transformers
pipeline_tag: text-generation
Naturecode Dhivehi 270m
The first open-source Dhivehi language model optimized for natural conversations.
Model Description
Naturecode Dhivehi 270m is a fine-tuned language model specifically designed for Dhivehi, the official language of the Maldives. Built on Google's FunctionGemma-270m architecture, this model has been trained through a 6-phase curriculum learning approach on authentic Dhivehi text data.
Key Features
- Native Dhivehi Support: Trained on authentic Dhivehi text including formal and informal language
- Conversational: Optimized for natural dialogue in Dhivehi
- Lightweight: 270M parameters - efficient for deployment
- Curriculum Trained: Progressive training through 6 phases for robust language understanding
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = AutoModelForCausalLM.from_pretrained("google/functiongemma-270m-it")
model = PeftModel.from_pretrained(base_model, "hilarl/naturecode-dhivehi-270m")
tokenizer = AutoTokenizer.from_pretrained("google/functiongemma-270m-it")
prompt = "<start_of_turn>user\nކިހިނެއް؟<end_of_turn>\n<start_of_turn>model\n"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))
Training Details
- Base Model: google/functiongemma-270m-it
- Training Method: LoRA fine-tuning with curriculum learning (6 phases)
- Training Data: Curated Dhivehi corpus including dictionary entries, formal text, informal conversations, and SFT data
Intended Use
- Dhivehi language chatbots and assistants
- Dhivehi text generation
- Educational applications for Dhivehi language learning
- Research on low-resource language models
Limitations
- Primarily trained for conversational use; may not excel at technical domains
- Performance may vary with highly specialized vocabulary
- Should not be used for generating harmful or misleading content
License
Apache 2.0
Citation
@misc{naturecode-dhivehi-270m,
author = {Naturecode},
title = {Naturecode Dhivehi 270m},
year = {2025},
publisher = {HuggingFace},
}