43 lines
1.1 KiB
Markdown
43 lines
1.1 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen3-4B
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tags:
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- biology
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- bio-posttrain
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- cpt
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library_name: transformers
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---
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# Bio-posttrain Qwen3-4B CPT
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Continued pre-training (CPT) checkpoint from [How Post-Training Shapes Biological Reasoning Models](https://huggingface.co/collections/mims-harvard/bio-posttrain).
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## Model details
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- **Base model:** `Qwen/Qwen3-4B`
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- **Stage:** CPT (text-only omics corpus)
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- **Training:** lr=1e-5, gradient accumulation=64, final CPT checkpoint
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("mims-harvard/bio-posttrain-qwen3-4b-cpt", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("mims-harvard/bio-posttrain-qwen3-4b-cpt", trust_remote_code=True)
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```
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## Collection
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Part of the [Bio-posttrain](https://huggingface.co/collections/mims-harvard/bio-posttrain) collection on Hugging Face.
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## Citation
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```bibtex
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@article{bio_posttrain_2026,
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title={How Post-Training Shapes Biological Reasoning Models},
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author={...},
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year={2026}
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}
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```
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