Instructions to use DeepChem/SmilesTokenizer_PubChem_1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepChem/SmilesTokenizer_PubChem_1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DeepChem/SmilesTokenizer_PubChem_1M")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DeepChem/SmilesTokenizer_PubChem_1M") model = AutoModel.from_pretrained("DeepChem/SmilesTokenizer_PubChem_1M") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
RoBERTa model trained on 1M SMILES from PubChem 77M set in MoleculeNet. Uses Smiles-Tokenizer
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