[Bug] the bug of generating Llama2 conversation template

Nobody has claimed this yet.

```python
# llama2 template
# reference: https://github.com/facebookresearch/llama/blob/cfc3fc8c1968d390eb830e65c63865e980873a06/llama/generation.py#L212
register_conv_template(
Conversation(
name="llama-2",
system_template="[INST] <>\n{system_message}\n<>\n\n",
roles=("[INST]", "[/INST]"),
messages=(),
offset=0,
sep_style=SeparatorStyle.LLAMA2,
sep=" ",
sep2=" ",
stop_token_ids=[2],
)
)
```
```python
def get_prompt(self) -> str:
#......
elif self.sep_style == SeparatorStyle.LLAMA2:
seps = [self.sep, self.sep2]
ret = ""
for i, (role, message) in enumerate(self.messages):
if message:
if i == 0:
ret += system_prompt + message
else:
ret += role + " " + message + seps[i % 2]
else:
ret += role
return ret
#......
```
when i=0, `ret += system_prompt + message`.However, when using preprocess function:
```python
def preprocess(
sources,
tokenizer: transformers.PreTrainedTokenizer,
) -> Dict:
# ......
sep = conv.sep + conv.roles[1] + ": "
for conversation, target in zip(conversations, targets):
# ......
parts = turn.split(sep)
```
`parts` can't be split by `seq`, because the `seq = " " + seps[i % 2]`.In fact, there is no this " " in `parts`

Start by comparing the LLAMA2 branch of get_prompt with preprocess, especially the generated separators and the string passed to split. Confirm the expected Llama2 conversation format from the linked reference, then make the prompt generation and preprocessing agree so the conversation is parsed successfully.

Written by the indexing model from the issue text.