gpt2-xl โ CE-FT-4 Single-Fact Edit
Model edited with CE-FT-4 (Circuit Entropy Regularization for Knowledge Editing).
Edit
| Prompt | The Eiffel Tower is located in the city of |
| Target | Berlin |
| Method | CE-FT-4 |
| Lambda | 10 |
| Edit success | True |
Training Config
| Parameter | Value |
|---|---|
| Steps | 20 |
| Learning rate | 1e-05 |
| Weight decay | 0.01 |
| Grad clip | 1.0 |
| Lambda (entropy) | 10 |
| EAP-IG steps | 5 |
| Seed | 42 |
Final Metrics
| Metric | Value |
|---|---|
| Final L_CE | 0.002533 |
| Final KL | 0.032956 |
| Final H(C) | 9.3347 |
| Final delta_H | 0.0293 |
Usage
from transformer_lens import HookedTransformer
import torch
model = HookedTransformer.from_pretrained("gpt2-xl")
state_dict = torch.load("model_state_dict.pt", map_location="cpu")
model.load_state_dict(state_dict)
tokens = model.to_tokens("The Eiffel Tower is located in the city of")
out = model.generate(tokens, max_new_tokens=10, do_sample=False)
print(model.tokenizer.decode(out[0]))
Paper
Circuit Entropy Regularization for Knowledge Editing (NeurIPS 2026 submission)
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