## Model Details

This is a fine-tuned ChemBERTa model trained for activity classification of potential NLRP3 inflammasome inhibitors. <br>
ChemBERTaNLRP3 was pre-trained on all currently known NLRP3 inhibitor data.
<br><br>
Supporting training and data files can be found in this GitHub repository: https://github.com/VitaRin/ChemBERTaNLRP3 <br>
Original pre-trained ChemBERTa model from which this model was fine-tuned can be found here: https://huggingface.co/seyonec/ChemBERTa-zinc250k-v1


## Example Use

This model can be further fine-tuned on more inhibitor data or used directly in a classification pipeline.<br>
A simple example usage of this model for molecular classification tasks:

```
from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
import pandas as pd
from datasets import Dataset

model_name = "VitaRin/ChemBERTaNLRP3"
smiles_data = ""

pipeline = TextClassificationPipeline(
    model=AutoModelForSequenceClassification.from_pretrained(model_name),
    tokenizer=AutoTokenizer.from_pretrained(model_name),
    device=0
)

test_df = pd.read_csv(smiles_data)
test_dataset = Dataset.from_pandas(test_df)
molecules = list(test_dataset["text"])

result = pipeline(molecules)

print(result)```