Instructions to use NbAiLab/borealis-4b-instruct-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NbAiLab/borealis-4b-instruct-preview with Transformers:

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

pipe = pipeline("image-text-to-text", model="NbAiLab/borealis-4b-instruct-preview")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("NbAiLab/borealis-4b-instruct-preview")
model = AutoModelForMultimodalLM.from_pretrained("NbAiLab/borealis-4b-instruct-preview")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NbAiLab/borealis-4b-instruct-preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NbAiLab/borealis-4b-instruct-preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NbAiLab/borealis-4b-instruct-preview",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/NbAiLab/borealis-4b-instruct-preview

SGLang

How to use NbAiLab/borealis-4b-instruct-preview 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 "NbAiLab/borealis-4b-instruct-preview" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NbAiLab/borealis-4b-instruct-preview",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "NbAiLab/borealis-4b-instruct-preview" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NbAiLab/borealis-4b-instruct-preview",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use NbAiLab/borealis-4b-instruct-preview with Docker Model Runner:
```
docker model run hf.co/NbAiLab/borealis-4b-instruct-preview
```

borealis-4b-instruct-preview / README.md

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	---
	license: gemma
	datasets:
	- NbAiLab/aurora-sft-2512-filtered
	language:
	- 'no'
	- nb
	- nn
	base_model:
	- google/gemma-3-4b-it
	pipeline_tag: image-text-to-text
	library_name: transformers
	tags:
	- conversational
	- instruct
	- experimental
	---

	# Borealis 4B Instruct (Preview)

	Release: Dec 22nd, 2025.

	## Model summary
	NbAiLab/borealis-4b-instruct-preview is a 4B-parameter instruction-tuned preview model intended for early testing and feedback. It is an experiment and should be treated as pre-release quality.

	This model is based on [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it), and fine-tuned on textual instructions only.

	\| Model \| Bits \| Format \|
	\|---\|---:\|---\|
	\| [NbAiLab/borealis-4b-instruct-preview](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview) \| BF16 \| Transformers (safetensors) \|
	\| [NbAiLab/borealis-4b-instruct-preview-gguf](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-gguf) \| 8 \| GGUF (`q8_0`) \|
	\| [NbAiLab/borealis-4b-instruct-preview-gguf](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-gguf) \| 16 \| GGUF (`f16`) \|
	\| [NbAiLab/borealis-4b-instruct-preview-gguf](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-gguf) \| BF16 \| GGUF (`bf16`) \|
	\| [NbAiLab/borealis-4b-instruct-preview-mlx](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-mlx) \| 32 \| MLX \|
	\| [NbAiLab/borealis-4b-instruct-preview-mlx-8bits](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-mlx-8bits) \| 8 \| MLX (quantized) \|

	## Training data
	Supervised fine-tuning (SFT) uses NbAiLab/aurora-sft-2512 (not released yet).

	## ⚠️ Safety / alignment disclaimer (important)
	This is a preview experiment and has not been safety-aligned yet. The model may produce harmful, biased, or insensitive outputs (including content that is offensive, unsafe, or inappropriate). Do not use it for safety-critical or high-stakes applications, and add your own safety mitigations if deploying.

	## Intended use
	- Norwegian-centric assistant-style tasks (e.g., drafting, summarization, Q&A, light reasoning).
	- Assesstment of Norwegian writing style and quality.
	- Early evaluation of behavior, language coverage (Norwegian / Bokmål / Nynorsk), and quality.

	## Limitations
	- Preview quality; outputs may be unstable and may hallucinate.
	- Not aligned for safety; may follow harmful instructions or generate problematic content (see disclaimer above).

	## Weights & formats

	### Transformers (original)
	- NbAiLab/borealis-4b-instruct-preview (safetensors).

	### GGUF quantizations
	Available in [NbAiLab/borealis-4b-instruct-preview-gguf](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-gguf):
	- `model-q8_0.gguf`
	- `model-f16.gguf`
	- `model-bf16.gguf`

	Use:
	```bash
	ollama run hf.co/NbAiLab/borealis-4b-instruct-preview-gguf:BF16
	```

	### MLX (Apple Silicon)
	Available in [NbAiLab/borealis-4b-instruct-preview-mlx](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-mlx) and quantized to [8 bits](https://huggingface.co/NbAiLab/borealis-4b-instruct-preview-mlx-8bits).

	Use:
	```bash
	# Install MLX LM
	uv tool install mlx-lm

	# Interactive chat REPL
	mlx_lm.chat --model "NbAiLab/borealis-4b-instruct-preview-mlx"
	```

	## Acknowledgements
	Thanks to the Gemma team at Google for releasing Gemma 3 and to everyone contributing feedback on this preview.