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README.md
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/npcomposer/npcomposer/runs/lpvwn86m)
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# NPComposer
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This model is a fine-tuned version of [ibm-research/GP-MoLFormer-Uniq](https://huggingface.co/ibm-research/GP-MoLFormer-Uniq) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2718
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/npcomposer/npcomposer/runs/lpvwn86m)
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# NPComposer
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NPComposer is a conditional molecular generation model trained by fine-tuning GP-MoLFormer — a 46.8M parameter transformer decoder foundation model — on the COCONUT database containing over 700,000 experimentally validated natural products.
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https://github.com/shawnralyn/NPComposer
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This model is a fine-tuned version of [ibm-research/GP-MoLFormer-Uniq](https://huggingface.co/ibm-research/GP-MoLFormer-Uniq) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2718
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