grad error using KnowledgeNeurons with model_name = "gpt2"

When I initialize KnowledgeNeurons with model_name = 'gpt2', I get an RuntimeError when trying to run kn.get_refined_neurons()

The following snippet would be able to reproduce the error on a colab notebook:
```
!pip install knowledge-neurons
!nvidia-smi
from knowledge_neurons import (
KnowledgeNeurons,
initialize_model_and_tokenizer,
model_type,
)
import random
import torch
import torch.nn.functional as F

# setup model, tokenizer + kn class
MODEL_NAME = "gpt2"
model, tokenizer = initialize_model_and_tokenizer(MODEL_NAME)
kn = KnowledgeNeurons(model, tokenizer,model_type(MODEL_NAME))

TEXT = "Sarah was visiting [MASK], the capital of france"
GROUND_TRUTH = "paris"
BATCH_SIZE = 10
STEPS = 20

ENG_TEXTS = [
"Sarah was visiting [MASK], the capital of france",
"The capital of france is [MASK]",
"[MASK] is the capital of france",
"France's capital [MASK] is a hotspot for romantic vacations",
"The eiffel tower is situated in [MASK]",
"[MASK] is the most populous city in france",
"[MASK], france's capital, is one of the most popular tourist destinations in the world",
]
FRENCH_TEXTS = [
"Sarah visitait [MASK], la capitale de la france",
"La capitale de la france est [MASK]",
"[MASK] est la capitale de la france",
"La capitale de la France [MASK] est un haut lieu des vacances romantiques",
"La tour eiffel est située à [MASK]",
"[MASK] est la ville la plus peuplée de france",
"[MASK], la capitale de la france, est l'une des destinations touristiques les plus prisées au monde",
]
TEXTS = ENG_TEXTS + FRENCH_TEXTS

refined_neurons_eng = kn.get_refined_neurons(
ENG_TEXTS,
GROUND_TRUTH,
p=P,
batch_size=BATCH_SIZE,
steps=STEPS,
)
refined_neurons_fr = kn.get_refined_neurons(
FRENCH_TEXTS,
GROUND_TRUTH,
p=P,
batch_size=BATCH_SIZE,
steps=STEPS,
)
refined_neurons = kn.get_refined_neurons(
TEXTS,
GROUND_TRUTH,
p=P,
batch_size=BATCH_SIZE,
steps=STEPS,
)
```

Given below is the full traceback:

```Getting coarse neurons for each prompt...: 0%| | 0/7 [00:00 in ()
45 p=P,
46 batch_size=BATCH_SIZE,
---> 47 steps=STEPS,
48 )
49 refined_neurons_fr = kn.get_refined_neurons(

5 frames
/usr/local/lib/python3.7/dist-packages/torch/autograd/__init__.py in _make_grads(outputs, grads)
49 if out.requires_grad:
50 if out.numel() != 1:
---> 51 raise RuntimeError("grad can be implicitly created only for scalar outputs")
52 new_grads.append(torch.ones_like(out, memory_format=torch.preserve_format))
53 else:

RuntimeError: grad can be implicitly created only for scalar outputs
```
Grad Error when initializing for the "gpt2" model
@StellaAthena @sdtblck also what should be the input and the target for "gpt2" model given it's autoregressive mechanism??