Text Generation
MLX
Safetensors
Norwegian
Norwegian Bokmål
Norwegian Nynorsk
gemma3
conversational
instruct
experimental
8-bit precision
🇪🇺 Region: EU
Instructions to use NbAiLab/borealis-4b-instruct-preview-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use NbAiLab/borealis-4b-instruct-preview-mlx-8bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("NbAiLab/borealis-4b-instruct-preview-mlx-8bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use NbAiLab/borealis-4b-instruct-preview-mlx-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "NbAiLab/borealis-4b-instruct-preview-mlx-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "NbAiLab/borealis-4b-instruct-preview-mlx-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NbAiLab/borealis-4b-instruct-preview-mlx-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Atomic Chat
metadata
license: gemma
datasets:
- NbAiLab/aurora-sft-2512-filtered
language:
- 'no'
- nb
- nn
base_model: NbAiLab/borealis-4b-instruct-preview
pipeline_tag: text-generation
library_name: mlx
tags:
- conversational
- instruct
- experimental
- mlx
Borealis 4B Instruct MLX (Preview)
Release: Dec 22nd, 2025.
Model summary
NbAiLab/borealis-4b-instruct-preview-mlx is a MLX 8bit quantized version of 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.
The original model is NbAiLab/borealis-4b-instruct-preview.
| Model | Bits | Format |
|---|---|---|
| NbAiLab/borealis-4b-instruct-preview | BF16 | Transformers (safetensors) |
| NbAiLab/borealis-4b-instruct-preview-gguf | 8 | GGUF (q8_0) |
| NbAiLab/borealis-4b-instruct-preview-gguf | 16 | GGUF (f16) |
| NbAiLab/borealis-4b-instruct-preview-gguf | BF16 | GGUF (bf16) |
| NbAiLab/borealis-4b-instruct-preview-mlx | 32 | MLX |
| NbAiLab/borealis-4b-instruct-preview-mlx-8bits | 8 | MLX (quantized) |
This model NbAiLab/borealis-4b-instruct-preview-mlx-8bits was converted to MLX format from NbAiLab/borealis-4b-instruct-preview using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("NbAiLab/borealis-4b-instruct-preview-mlx-8bits")
prompt = "hei :)"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)