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This model is an example of how a fine-tuned LLM even without the full depth, size, and complexity of larger and more expensive models can be useful in context-sensitive situations. In our use-case, we are applying this LLM as part of a broader electronic lab notebook software setup for molecular and computational biologists. This GPT-2 has been finetuned on datasets from BioASQ and PubMedQA and is now knowledgeable enough in biochemistry to assist scientists and integrates as not just a copilot-like tool but also as a lab partner to the overall Design-Built-Test-Learn workflow ever growing in prominence in synthetic biology. |
