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README.md
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@@ -5,9 +5,22 @@ This repository contains the model weights of the BERT model trained by predicti
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Further information can be found in our [publication](https://arxiv.org/abs/2503.03360).
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```python
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from transformers import AutoModel
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```
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Further information can be found in our [publication](https://arxiv.org/abs/2503.03360).
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```python
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from transformers import AutoModel, AutoTokenizer
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mols = [
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"CCOc1cc2nn(CCC(C)(C)O)cc2cc1NC(=O)c1cccc(C(F)F)n1",
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"CN(c1ncc(F)cn1)[C@H]1CCCNC1",
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"CC(C)(Oc1ccc(-c2cnc(N)c(-c3ccc(Cl)cc3)c2)cc1)C(=O)O",
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"CC(C)(O)CCn1cc2cc(NC(=O)c3cccc(C(F)(F)F)n3)c(C(C)(C)O)cc2n1",
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# ...
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]
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tokenizer = AutoTokenizer.from_pretrained("UdS-LSV/da4mt-mtr-60")
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model = AutoModel.from_pretrained("UdS-LSV/da4mt-mtr-60")
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inputs = tokenizer(mols, add_special_tokens=True, truncation=True, max_length=128, padding="max_length", return_tensors="pt")
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embeddings = model(**inputs).last_hidden_state[:, 0, :]
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```
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