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Paper: https://arxiv.org/abs/2311.16208
Part of the community sprint #9694
The goal of this project is to reproduce the work done in InstructMol while tying it as closely to the existing GNN+LLM frameworks in PyG. We recommend using as many existing features as possible from PyG. Additional features which you feel will be reusable for other workflows should be added to PyG. One-off functions that are specific to this workflow can be left inside the example.
Most of the effort will likely go into building a PyG dataset that matches the one described in the paper. At a high level the dataset is a composition of Q+A pairs mimicking a drug discovery agent workflow, with matching drug graphs.
Alternatives
No response
Additional context
No response
The text was updated successfully, but these errors were encountered:
🚀 The feature, motivation and pitch
Paper: https://arxiv.org/abs/2311.16208
Part of the community sprint #9694
The goal of this project is to reproduce the work done in
InstructMol
while tying it as closely to the existing GNN+LLM frameworks in PyG. We recommend using as many existing features as possible from PyG. Additional features which you feel will be reusable for other workflows should be added to PyG. One-off functions that are specific to this workflow can be left inside the example.Most of the effort will likely go into building a PyG dataset that matches the one described in the paper. At a high level the dataset is a composition of Q+A pairs mimicking a drug discovery agent workflow, with matching drug graphs.
Alternatives
No response
Additional context
No response
The text was updated successfully, but these errors were encountered: