Instructions to use pi-dal/Linnaeus-0.1.0-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pi-dal/Linnaeus-0.1.0-2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pi-dal/Linnaeus-0.1.0-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -24,14 +24,15 @@ Built on Qwen/Qwen3.5-2B, this checkpoint returns decision distributions from te
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## On-device exports (Apple Silicon)
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Merged + quantized builds for macOS/iOS (text
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is not ported to MLX):
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| Repo | Size | JevBench | Target |
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| [Linnaeus-0.1.0-2B-merged](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-merged) | 4.3 GB | 71.0% (MPS) | Mac dev / conversion source |
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| [Linnaeus-0.1.0-2B-MLX-8bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-8bit) | 1.9 GB | 70.56% | Mac + iPhone |
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| [Linnaeus-0.1.0-2B-MLX-4bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-4bit) | 1.0 GB | 67.53% | iPhone size-optimized |
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The merged checkpoint embeds the decision head as an extra lm_head row
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(score_row_id), so any stock LM runtime produces decision scores at
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## On-device exports (Apple Silicon)
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Merged + quantized builds for macOS/iOS (text MLX builds are text-only; the VLM builds keep the vision tower):
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| Repo | Size | JevBench | Target |
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| --- | --- | --- | --- |
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| [Linnaeus-0.1.0-2B-merged](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-merged) | 4.3 GB | 71.0% (MPS) | Mac dev / conversion source |
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| [Linnaeus-0.1.0-2B-MLX-8bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-8bit) | 1.9 GB | 70.56% | Mac + iPhone |
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| [Linnaeus-0.1.0-2B-MLX-4bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-4bit) | 1.0 GB | 67.53% | iPhone size-optimized |
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| [Linnaeus-0.1.0-2B-MLX-VLM-8bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-VLM-8bit) | 2.5 GB | text 70.56% + **images** | Mac + iPhone multimodal |
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| [Linnaeus-0.1.0-2B-MLX-VLM-4bit](https://huggingface.co/pi-dal/Linnaeus-0.1.0-2B-MLX-VLM-4bit) | 1.6 GB | text ~67% + **images** | iPhone multimodal, size pick |
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The merged checkpoint embeds the decision head as an extra lm_head row
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(score_row_id), so any stock LM runtime produces decision scores at
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