Instructions to use emrevrg/AUBIN-E4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use emrevrg/AUBIN-E4B with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-E4B-it")
model = PeftModel.from_pretrained(base_model, "emrevrg/AUBIN-E4B")

Transformers

How to use emrevrg/AUBIN-E4B with Transformers:

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

pipe = pipeline("text-generation", model="emrevrg/AUBIN-E4B")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("emrevrg/AUBIN-E4B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use emrevrg/AUBIN-E4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "emrevrg/AUBIN-E4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "emrevrg/AUBIN-E4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/emrevrg/AUBIN-E4B

SGLang

How to use emrevrg/AUBIN-E4B 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 "emrevrg/AUBIN-E4B" \
    --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": "emrevrg/AUBIN-E4B",
		"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 "emrevrg/AUBIN-E4B" \
        --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": "emrevrg/AUBIN-E4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use emrevrg/AUBIN-E4B with Docker Model Runner:
```
docker model run hf.co/emrevrg/AUBIN-E4B
```

Model Card for Model ID

🔬 Preview — This model is under active development; stronger versions will be released in this repository.

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Framework versions

PEFT 0.21.1

Support Norovox

Norovox is built by one 17-year-old high school student in Türkiye: no company, no sponsor, no budget. Every model on this page was trained on free GPU quotas that run out within days. When they run out, training stops halfway and the next, stronger version has to wait, sometimes for a week.

Your support goes directly into GPU time. Even a small contribution lets a training run finish instead of stopping, and helps the Nythos, N1, AUBIN and Norovox Embed models get better faster. Supporters are credited in the model cards and get early access to new releases.

Contact: zgremre@gmail.com · emrevrgdev@gmail.com

_{🇹🇷 Norovox'u Türkiye'de 17 yaşında bir lise öğrencisi tek başına geliştiriyor: şirket yok, sponsor yok, bütçe yok. Buradaki modellerin hepsi birkaç günde biten ücretsiz GPU kotalarıyla eğitildi; kota bitince eğitim yarıda kalıyor ve daha güçlü sürüm bekliyor. Desteğin doğrudan GPU süresine gider; küçük bir katkı bile bir eğitimin yarıda kalmadan tamamlanmasını sağlar. Destekçiler model kartlarında anılır ve yeni sürümlere erken erişir. İletişim: zgremre@gmail.com · emrevrgdev@gmail.com}

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Model tree for emrevrg/AUBIN-E4B

Base model

google/gemma-4-E4B

Finetuned

google/gemma-4-E4B-it

Adapter

(413)

this model

Collection including emrevrg/AUBIN-E4B

AUBIN

Collection

AUBIN: Norovox Labs' decision and agent models (Mini, Omni, E4B, 12B, 31B). • 15 items • Updated 2 days ago • 1

Paper for emrevrg/AUBIN-E4B

Quantifying the Carbon Emissions of Machine Learning

Paper • 1910.09700 • Published Oct 21, 2019 • 61