Instructions to use Parsa/BBB_prediction_classification_SMILES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Parsa/BBB_prediction_classification_SMILES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Parsa/BBB_prediction_classification_SMILES")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Parsa/BBB_prediction_classification_SMILES") model = AutoModelForSequenceClassification.from_pretrained("Parsa/BBB_prediction_classification_SMILES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (b07ca6248faecc4572986efa60c0d2c9c9ca14b3) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c0997bc
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A fine-tuned model based on 'DeepChem/ChemBERTa-77M-MLM' for blood-brain-barrier permeability prediction based on SMILES strings269a0dc -
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