ICM

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "beingamanforever/ICM"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

questions = [
    "What is the distance between the two trees?",
    "Describe what the child is wearing.",
    "Is the traffic light green?",
    "Box the location of the blue umbrella."
]

inputs = tokenizer(questions, return_tensors="pt", padding=True, truncation=True)
with torch.no_grad():
    logits = model(**inputs).logits
    predictions = torch.argmax(logits, dim=-1)

for q, pred in zip(questions, predictions):
    print(f"{q} → {model.config.id2label[pred.item()]}")