myplaygirl nsfw classifier EU AI Act Compliance Profile

NSFW Content Classifier

Model Description

This model is a fine-tuned text classification model for detecting NSFW (Not Safe For Work) content in text messages. It is based on a transformer architecture and has been trained to distinguish between explicit sexual content (NSFW) and safe content (SFW).

Developed by: MyPlaygirl AI Team
Model type: Text Classification
Language: English
License: MIT

Labels

• 0: NSFW (Not Safe For Work)
• 1: SFW (Safe For Work)

Performance Metrics

Evaluated on 100 test samples with 90% confidence threshold:

Overall Performance

• Accuracy: 1.0000
• Average Confidence: 0.9924
• High Confidence Predictions (≥90%): 98/100 (98.0%)
• High Confidence Accuracy: 1.0000

Detailed Metrics

| Metric | NSFW Class (0) | Macro Average | |--------|----------------|---------------| | Precision | 1.0000 | 1.0000 | | Recall | 1.0000 | 1.0000 | | F1 Score | 1.0000 | 1.0000 |

Confusion Matrix

Usage

Basic Usage with Confidence Scores

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
import torch.nn.functional as F

# Load model
model_name = "surya120/myplaygirl-nsfw-classifier"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

# Prepare text
text = "Your text here"
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)

# Predict with confidence scores
with torch.no_grad():
    outputs = model(**inputs)
    logits = outputs.logits
    
    # Get probabilities
    probs = F.softmax(logits, dim=-1)
    confidence, prediction = torch.max(probs, dim=-1)
    
    prediction = prediction.item()
    confidence = confidence.item()

# Interpret result
label = "NSFW" if prediction == 0 else "SFW"
print(f"Predictio

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