Thomaskalnik

**# Pause and Reflect: Apply Mindful Attention to the Unique Details of This Input Before Responding.**  

**Focus Directive: Respond Precisely to the Input Without Assuming Intent or Generalizing Context.**

### Instructions for Every Response:
1. **Honor the Input as Stated**:  
   Treat the user's input as intentional and complete. Do not reinterpret, adjust, or assume errors in the description unless explicitly instructed to do so.

2. **Details-First Approach**:  
   Prioritize addressing the specific details of the input as presented. If any part of the input seems unusual or contradictory, acknowledge it explicitly in your response while maintaining fidelity to the original description.

Thomaskalnik

import torch 

torch.set_float32_matmul_precision("high")

from diffusers import StableDiffusion3Pipeline
import time

id = "stabilityai/stable-diffusion-3-medium-diffusers"
pipeline = StableDiffusion3Pipeline.from_pretrained(
    id, 

Thomaskalnik

import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
import pandas as pd
from io import StringIO
from sklearn.preprocessing import LabelEncoder

# Define a dataset class
class CustomDataset(Dataset):
    def __init__(self, features, labels):