from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch

model_id = "contributor-anonymous/Mol2Pro-base"
tokenizer_id = "contributor-anonymous/Mol2Pro-tokenizer"

# Load tokenizers
tokenizer_mol = AutoTokenizer.from_pretrained(tokenizer_id, subfolder="smiles")
tokenizer_aa  = AutoTokenizer.from_pretrained(tokenizer_id, subfolder="aa")

# Load model
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)

Intended use

Research use only. The model generates candidate sequences conditioned on small-molecule inputs; it does not guarantee binding or function and must be validated experimentally.