Instructions to use jonghyunlee/ChemBERT_ChEMBL_pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonghyunlee/ChemBERT_ChEMBL_pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jonghyunlee/ChemBERT_ChEMBL_pretrained")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jonghyunlee/ChemBERT_ChEMBL_pretrained") model = AutoModel.from_pretrained("jonghyunlee/ChemBERT_ChEMBL_pretrained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Pretraining Database
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The model was pretrained using data from the ChEMBL database, specifically version 33. You can download the database from [ChEMBL](https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/latest/).
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- Optimizer: AdamW
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- Learning rate: 1e-4
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- Learning rate scheduler: False
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- Epochs: 50
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- AMP: True
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- GPU: Single Nvidia RTX 3090
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## Pretraining Database
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The model was pretrained using data from the ChEMBL database, specifically version 33. You can download the database from [ChEMBL](https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/latest/).
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