41 lines
1.2 KiB
Markdown
41 lines
1.2 KiB
Markdown
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---
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license: mit
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- biology
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- plasmid
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- dna
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- synthetic-biology
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- gpt2
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---
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# PlasmidGPT
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A HuggingFace-compatible repackaging of [PlasmidGPT](https://github.com/lingxusb/PlasmidGPT) (Shao, 2024) — a GPT-2-style decoder pretrained on 153k engineered plasmid sequences from Addgene. Loadable with standard `AutoModelForCausalLM` and `AutoTokenizer`. Used as the base for [PlasmidGPT-SFT](https://huggingface.co/UCL-CSSB/PlasmidGPT-SFT) and [PlasmidGPT-GRPO](https://huggingface.co/UCL-CSSB/PlasmidGPT-GRPO).
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## Quick start
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("UCL-CSSB/PlasmidGPT")
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tokenizer = AutoTokenizer.from_pretrained("UCL-CSSB/PlasmidGPT")
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input_ids = tokenizer("ATG", return_tensors="pt").input_ids
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outputs = model.generate(input_ids, max_new_tokens=512, do_sample=True, temperature=1.0)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Citation
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```bibtex
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@article{shao2024plasmidgpt,
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title = {{PlasmidGPT}: a generative framework for plasmid design and annotation},
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author = {Shao, Bin},
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journal = {bioRxiv},
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year = {2024},
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doi = {10.1101/2024.09.30.615762}
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}
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```
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