| license: mit | |
| datasets: | |
| - lisn519010/QM9 | |
| language: | |
| - en | |
| metrics: | |
| - mae | |
| - accuracy | |
| - mse | |
| - r_squared | |
| pipeline_tag: graph-ml | |
| ``` | |
| pip install torch_scatter rdkit | |
| pip install torch_geometric | |
| ``` | |
| ### example | |
| ```python | |
| from transformers import AutoModel | |
| device = 'cpu' | |
| smiles = ['CCCC', 'C#C/C(C)=C(/[CH2])C', 'NNNNN'] | |
| model = AutoModel.from_pretrained("Huhujingjing/custom-gcn", trust_remote_code=True).to(device) | |
| output = model.predict_smiles(smiles) | |
| print(output) | |
| ``` |