53 lines
1.6 KiB
Markdown
53 lines
1.6 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen3-1.7B
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tags:
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- biology
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- bio-posttrain
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- dna-sft
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- dna
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library_name: transformers
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---
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# Bio-posttrain Qwen3-1.7B DNA SFT
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DNA supervised fine-tuning (SFT) 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/Qwen3-1.7B`
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- **DNA encoder:** Evo2 `evo2_1b_base` (frozen; not included in this repo)
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- **Embedding layer:** `blocks.20.mlp.l3`
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- **LoRA:** rank 64, alpha 128
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- **Validation loss:** 0.4687
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This repo contains the **merged text LLM** (LoRA fused into base weights) plus `dna_projection.pt`.
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## Files
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| File | Description |
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|------|-------------|
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| `model.safetensors` | Merged Qwen3-1.7B weights |
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| `dna_projection.pt` | Linear map from Evo2 hidden (1920) → text hidden (2048) |
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| `dna_model_config.json` | DNA encoder + projection metadata |
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## Loading
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Use the [BioReason](https://github.com/mims-harvard/BioReason) `DNALLMModel` loader:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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text_model = AutoModelForCausalLM.from_pretrained("mims-harvard/bio-posttrain-qwen3-1.7b-dna-sft")
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tokenizer = AutoTokenizer.from_pretrained("mims-harvard/bio-posttrain-qwen3-1.7b-dna-sft")
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proj = torch.load("mims-harvard/bio-posttrain-qwen3-1.7b-dna-sft/dna_projection.pt", map_location="cpu")
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# Load Evo2 separately: evo2_1b_base
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```
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See `dna_model_config.json` for encoder settings.
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## Collection
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Part of the [Bio-posttrain](https://huggingface.co/collections/mims-harvard/bio-posttrain) collection.
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