Instructions to use nepp1d0/SingleBertSmilesTargetInteraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/SingleBertSmilesTargetInteraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nepp1d0/SingleBertSmilesTargetInteraction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nepp1d0/SingleBertSmilesTargetInteraction") model = AutoModelForSequenceClassification.from_pretrained("nepp1d0/SingleBertSmilesTargetInteraction") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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Prot_bert finetuned on GPCR_train dataset of Drug Target prediction
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Trainig paramenters:
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overwrite_output_dir=True,
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evaluation_strategy="epoch",
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learning_rate=1e-3,
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weight_decay=0.001,
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per_device_train_batch_size=batch_size,
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per_device_eval_batch_size=batch_size,
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push_to_hub=True,
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fp16=True,
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logging_steps=logging_steps,
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save_strategy='epoch',
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num_train_epochs=2
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