license: other
license_name: armeniangpt-license-0.5
license_link: LICENSE
language:
- hy
- ru
- en
pipeline_tag: text-generation
tags:
- First
- Armenian
- Am
- Hayeren
- Hy
- Russian
- English
- Reasoning
- Thinking
- LLM
ArmenianGPT v0.5 - Second Iteration Of The First Ever Armenian Reasoning Model
Now With Adaptive Reasoning Intelligence
Developed by Aleksandr Baghramyan
This second version (v0.5) of ArmenianGPT, the first-ever Armenian reasoning model (not only responding, but also thinking natively in Armenian), is currently in a progressive training phase, with more powerful models of various sizes trained on a broader range of disciplines expected soon; to contribute, please send a screenshot or text of your questions along with the model's answers to [email protected] for us to analyze and prevent such errors in future iterations of this model line.
This model represents a breakthrough in natural language processing for the Armenian language by enabling natural communication through its unique ability to process prompts typed with English characters - a popular, faster, and more convenient method for many users.
Configurations for Optimal Model Performance
A temperature of 0 is recommended for this iteration of the model.
| Desired Output | Recommended Temperature | Use Case Examples |
|---|---|---|
| High Accuracy & Factual Precision | 0.0 - 0.3 |
Factual question answering, code generation, summarization. |
| Creative & Diverse Responses | 0.3 - 1.0 |
Brainstorming ideas, creative writing, exploring solutions to complex problems. |
Running the Model on a Single / Multi GPU
# pip install -U transformers
# pip install accelerate
from transformers import AutoProcessor, Gemma3ForConditionalGeneration
from huggingface_hub import login
from PIL import Image
import requests
import torch
HUGGINGFACE_TOKEN = "YOUR HUGGINGFACE TOKEN GOES HERE"
login(token=HUGGINGFACE_TOKEN)
model_id = "ArmGPT/ArmenianGPT-0.5-12B"
model = Gemma3ForConditionalGeneration.from_pretrained(
model_id, device_map="auto"
).eval()
processor = AutoProcessor.from_pretrained(model_id)
messages = [
{
"role": "system",
"content": [{"type": "text", "text": "You are an Armenian AI assistant who always thinks before providing the final response."}]
},
{
"role": "user",
"content": [{"type": "text", "text": "YOUR QUESTION/PROBLEM IN ARMENIAN GOES HERE"}]
}
]
inputs = processor.apply_chat_template(
messages, add_generation_prompt=True, tokenize=True,
return_dict=True, return_tensors="pt"
).to(model.device, dtype=torch.bfloat16)
input_len = inputs["input_ids"].shape[-1]
with torch.inference_mode():
generation = model.generate(**inputs, max_new_tokens=5799, do_sample=False)
generation = generation[0][input_len:]
decoded = processor.decode(generation, skip_special_tokens=True)
print(decoded)