Slop Classifier for Roleplay Characters
This model can detect characters that are created using AI.
Part of CharGen project - it is used to detect and filter out low-effort, LLM-made characters intended for role playing.
Slop refers to over-used phrases that models like GPT3.5 like to use very much and that do not add any value to the text. "Shivers down her spine", "enigma wrapped in mystery", "half-lidded eyes", etc. Classifier is trained on set of synthetic characters generated with GPT3.5 and GPT4, and a subset of CharGen dataset.
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
from litserve import LitAPI, LitServer
MODEL_NAME = "kubernetes-bad/character-slop-classifier"
class CHARLitAPI(LitAPI):
def setup(self, device):
self.tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
self.model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
self.model.to(device)
self.model.eval()
def decode_request(self, request):
if "text" in request:
inputs = self.tokenizer(request["text"], return_tensors="pt", padding=True, truncation=True, max_length=512)
elif "texts" in request:
inputs = self.tokenizer(request["texts"], return_tensors="pt", padding=True, truncation=True, max_length=512)
else:
raise ValueError("Invalid request format. Expected 'text' or 'texts' field.")
return inputs
def predict(self, inputs):
with torch.no_grad():
inputs = {k: v.to(self.model.device) for k, v in inputs.items()}
outputs = self.model(**inputs)
return outputs.logits
def encode_response(self, logits):
probabilities = torch.nn.functional.softmax(logits, dim=-1)
if probabilities.shape[0] == 1:
response = {
"positive": probabilities[:, 1].item(),
"negative": probabilities[:, 0].item()
}
else:
response = [
{
"positive": prob[1].item(),
"negative": prob[0].item()
}
for prob in probabilities
]
return response
if __name__ == "__main__":
api = CHARLitAPI()
server = LitServer(api, accelerator='cuda')
server.run(port=9000)
curl --location 'http://localhost:9000/predict' \
--header 'Content-Type: application/json' \
--data '{
"text": "Hermione, the seductive intellectual enchantress, is the secret sin of Hogwarts. Beneath her seemingly innocent scholarly facade lies a tantalizing world of forbidden desires. In the hallowed halls of the wizarding world, she conceals her lewd nature from her peers, maintaining a pristine reputation as the most brilliant witch of her age."
}'
Example response:
{
"positive": 0.9975564479827881,
"negative": 0.0024435613304376602
}