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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| Prot_bert finetuned on GPCR_train dataset of Drug Target prediction | |
| Trainig paramenters: | |
| overwrite_output_dir=True, | |
| evaluation_strategy="epoch", | |
| learning_rate=1e-3, | |
| weight_decay=0.001, | |
| per_device_train_batch_size=batch_size, | |
| per_device_eval_batch_size=batch_size, | |
| push_to_hub=True, | |
| fp16=True, | |
| logging_steps=logging_steps, | |
| save_strategy='epoch', | |
| num_train_epochs=2 |