| license: gemma | |
| datasets: | |
| - NbAiLab/aurora-sft-2512-filtered | |
| language: | |
| - 'no' | |
| - nb | |
| - nn | |
| base_model: NbAiLab/borealis-1b-instruct-preview | |
| pipeline_tag: image-text-to-text | |
| library_name: transformers | |
| tags: | |
| - conversational | |
| - instruct | |
| - experimental | |
| - mlx | |
| - mlx-my-repo | |
| # Borealis 1B Instruct Preview MLX | |
| Converted to **MLX** from [NbAiLab/borealis-1b-instruct-preview](https://huggingface.co/NbAiLab/borealis-1b-instruct-preview) using `mlx-lm` **0.29.1**. | |
| **Repo:** https://huggingface.co/NbAiLab/borealis-1b-instruct-preview-mlx | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("NbAiLab/borealis-1b-instruct-preview-mlx") | |
| prompt = "hei :)" | |
| if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: | |
| messages = [{"role": "user", "content": prompt}] | |
| prompt = tokenizer.apply_chat_template( | |
| messages, tokenize=False, add_generation_prompt=True | |
| ) | |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
| print(response) | |
| ``` | |