Instructions to use ai-forever/mGPT-1.3B-bashkir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ai-forever/mGPT-1.3B-bashkir with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ai-forever/mGPT-1.3B-bashkir")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ai-forever/mGPT-1.3B-bashkir")
model = AutoModelForCausalLM.from_pretrained("ai-forever/mGPT-1.3B-bashkir")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ai-forever/mGPT-1.3B-bashkir with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ai-forever/mGPT-1.3B-bashkir"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ai-forever/mGPT-1.3B-bashkir",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ai-forever/mGPT-1.3B-bashkir

SGLang

How to use ai-forever/mGPT-1.3B-bashkir with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ai-forever/mGPT-1.3B-bashkir" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ai-forever/mGPT-1.3B-bashkir",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ai-forever/mGPT-1.3B-bashkir" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ai-forever/mGPT-1.3B-bashkir",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ai-forever/mGPT-1.3B-bashkir with Docker Model Runner:
```
docker model run hf.co/ai-forever/mGPT-1.3B-bashkir
```

🍯 Bashkir mGPT 1.3B

Language model for Bashkir. Model has 1.3B parameters as you can guess from it's name.

Bashkir belongs to Turkic language family. It's a very unique language with approximately 1.2 million speakers. Here are some facts about it:

It is primarily spoken in Bashkortostan, Russia.
It uses the Cyrillic script.
It has been influenced by Tatar and Chuvash languages.

Technical details

It's one of the models derived from the base mGPT-XL (1.3B) model (see the list below) which was originally trained on the 61 languages from 25 language families using Wikipedia and C4 corpus.

We've found additional data for 23 languages most of which are considered as minor and decided to further tune the base model. Bashkir mGPT 1.3B was trained for another 5000 steps with batch_size=4 and context window of 2048 tokens on 1 A100.

Final perplexity for this model on validation is 7.06.

Chart of the training loss and perplexity:

Other mGPT-1.3B models

Feedback

If you'll found a bug of have additional data to train model on your language — please, give us feedback.

Model will be improved over time. Stay tuned!

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