model = transformers.AutoModelForSequenceClassification.from_pretrained('edmundmills/experience-model-v1')  # type: ignore
tokenizer = transformers.AutoTokenizer.from_pretrained('edmundmills/experience-model-v1', use_fast=False)  # type: ignore
sentence = "I am eating food."
tokenized = tokenizer([sentence], return_tensors='pt', return_attention_mask=True)
input_ids, masks = tokenized['input_ids'], tokenized['attention_mask']
with torch.inference_mode():
    out = model(input_ids, attention_mask=masks)
probs = out.logits.sigmoid().squeeze().item()
print(probs) # 0.92