# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("DeepChem/ChemBERTa-100M-MLM")
model = AutoModelForMaskedLM.from_pretrained("DeepChem/ChemBERTa-100M-MLM")Quick Links
ChemBERTa-100M-MLM
ChemBERTa model pretrained on a subset of 100M molecules from ZINC20 dataset using masked language modeling (MLM).
Usage
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("DeepChem/ChemBERTa-100M-MLM")
model = AutoModelForMaskedLM.from_pretrained("DeepChem/ChemBERTa-100M-MLM")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DeepChem/ChemBERTa-100M-MLM")