This is a DeBERTa-V3 condition checker distilled from GPT-4.1:
Base model (0.1B, 71% consistency with GPT-4.1): this link
The dataset (20,759 cases) for distillation can be accessed via this link
How to use?
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
# Load Condition Checker
classifier_path = "KomeijiForce/deberta-v3-large-check-scene"
classifier_tokenizer = AutoTokenizer.from_pretrained(classifier_path)
classifier = AutoModelForSequenceClassification.from_pretrained(classifier_path)
# Formalize Condition Checking into Prompt
scene = "Koishi quietly emerged from behind the dense foliage, her sudden appearance catching the corner of Satori's eye as she stepped into the direct line of vision, smiling mischievously."
question = "Does Koishi enter someone's direct field of vision?"
prompt = f'''Scene: {scene}
Question: {question}
Directly answer only yes/no/unknown.'''
# Scoring and Decoding
with torch.no_grad():
logits = classifier(**classifier_tokenizer(prompt, return_tensors="pt")).logits[0]
choice = logits.argmax(-1).item()
answer = [False, None, True][choice]
print(answer)
# True
- Downloads last month
- 24
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support