Instructions to use JuIm/BERT_SMILES_LARGE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuIm/BERT_SMILES_LARGE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JuIm/BERT_SMILES_LARGE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JuIm/BERT_SMILES_LARGE") model = AutoModelForMaskedLM.from_pretrained("JuIm/BERT_SMILES_LARGE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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model-index:
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- name: ROBERTA_SMILES_LARGE
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results: []
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---
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model-index:
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- name: ROBERTA_SMILES_LARGE
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results: []
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- text: OC<mask>C=CC2C34C1Oc1c4c(CC2N(CC3)C)ccc1O
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pipeline_tag: fill-mask
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