Generated code get's corrupted in post process

ChatGPT Bugs
1

I’ve asked chatgpt to generate some sample code distill an embedding model and this is what I got

import torch
import torch.nn as nn
from transformers import AutoTokenizer, AutoModel
from datasets import load_dataset
from torch.utils.data import DataLoader, Dataset

# 1️⃣ Load an NLI dataset with pair-class subset
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# hf_ds now contains 'premise', 'hypothesis', 'label' fields :contentReference[oaicite:2]{index=2}

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# 2️⃣ Load teacher and student models
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# 3️⃣ Mean pooling function
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# 4️⃣ Set up training
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# 5️⃣ Training loop
model_S.train()
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        # Teacher embeddings
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        # Student embeddings
        inp_S = tok_S(batch, padding=True, truncation=True, return_tensors="pt").to(device)
        out_S = model_S(**inp_S)
        emb_S = nn.functional.normalize(mean_pool(out_S.last_hidden_state, inp_S.attention_mask), dim=1)
        
        # Cosine loss
        labels = torch.ones(emb_T.size(0), device=device)
        loss = loss_fn(emb_S, emb_T, labels)
        
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
        epoch_loss += loss.item()
    
    avg_loss = epoch_loss / len(loader)
    print(f"[Epoch {epoch+1}] Avg Cosine Loss: {avg_loss:.4f}")

The code was actually generated correctly at first but after the generation was done it was corrupted with these contentReference tags