from transformers import AutoTokenizer, AutoModel
import torch

model_name = "nawazishpatana/claim-detector-brain-tumor"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)

text = "Our model achieved 95% accuracy."
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)

Ablations

SciBERT+Context: F1=0.8003
SciBERT: F1=0.7483
PubMedBERT+Context: F1=0.7813

Training Config

Optimizer: AdamW (LR backbone=2e-05, head=0.001)
Loss: CrossEntropyLoss + label smoothing=0.1
Early stopping: patience=3
Context: Yes