Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained
Author: yingqianch
Pull request: no

### System Info

Hello, I am running the qwen-1.5-0.5B-Chat model . According to https://modelscope.cn/models/qwen/Qwen1.5-0.5B-Chat/summary , at the Qickstart part ,
```python3
from modelscope import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained(
    "qwen/Qwen1.5-0.5B-Chat",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("qwen/Qwen1.5-0.5B-Chat")

prompt = "Give me a short introduction to large language model."
messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
```
I put the code in run_qwen-1.5-0.5B-Chat.py, when I run  run_qwen-1.5-0.5B-Chat.py, I get the warning : Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained .And then there's no output. I don't know how to solve the warning. 

### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

from modelscope import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained(
    "qwen/Qwen1.5-0.5B-Chat",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("qwen/Qwen1.5-0.5B-Chat")

prompt = "Give me a short introduction to large language model."
messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]

### Expected behavior

Does anyone else run into the same problem with qwen-1.5-0.5B-Chat model? If anyone knows the solution to this problem, please let me know, I would be very grateful.

Comments:
cc @ArthurZucker 

Hey! You are using `modelscope` which is not `transformers`. 
Anyway the warning just means that there are special tokens added to the tokenizer, more often than not the word embeddings are already correctly resized

@ArthurZucker , i got a bit confused by your response . Please correct me if im wrong . The models embedding size doesnt need to be resized in the mentioned code since the tokenizer already has the instruction tokens added .

print(response)

It does, if you add the token to the tokenizer, you increase the vocab size. But if you don't do the equivalent operation for the embedding matrix, then you are gonna go over the dimension of the embedding matrix! 

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.

I have the same issue

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.

I am facing the same issue for loading finetuned saved llava1.5 model.

Hey, it's not an issue and is expected depending on the.version of transformers. We removed the warning two releases ago! 

Yes! I find this warning is not an error. The reason I think this is an error is because I ran the program without any output. Just add "print(response)" to the last line of your python script and you'll see the output.

> Hey, it's not an issue and is expected depending on the.version of transformers. We removed the warning two releases ago!

Yes! I find this warning is not an error. The reason I think this is an error is because I ran the program without any output. Just add "print(response)" to the last line of your python script and you'll see the output.