Feature to highlight or color code the text from the NER output of token classification having offsets using python
### Feature request

I have fine tuned a `Hugging face` `token classification` model for `NER task`. I use `pipeline` from Hugging face to do prediction on test text data.

I tag the data as `BIOL` format. `B stands of Beginning, I stand for Including, O means no entity, L means Last`

**Example:**

`Joh J Mathew` will be tagged as `B_PERSON` `I_PERSON` `L_PERSON`

**Here is how the output looks like:**

    model = AutoModelForTokenClassification.from_pretrained("model_x")
    tokenizer = AutoTokenizer.from_pretrained("model_x")
        
    token_classifier = pipeline("token-classification", model=model, aggregation_strategy="max",tokenizer=tokenizer)
    
    text=("""'IOWA DRIVER LICENSE 1 SAMPLE 2 MARK LIMITED-TERM 8 123 NORTH STREET APT 201 DES MOINES, IA 50301-1234 
    Onom d DL No. 123XX6789 4a iss 1107/2016 4b exp 01/12/2021 15 Sex M 16 Hgt 5\'-08" 18 Eyes BRO 9a End NONE 9 
    Class C 12 Rest NONE Mark Sample DONOR MED ALERT: Y HEARING IMP: Y MED ADV DIR: Y 3 OOB 01/12/1967 5 
    DD 12345678901234567890123 NIVIA AL NA LANG ---- QUE EROL DE USA 01/12/67""")
    
    for ent in token_classifier(text):
        print(ent)
    
    {'entity_group': 'B_LAST_NAME', 'score': 0.9999994, 'word': 'SAMPLE', 'start': 23, 'end': 29}
    {'entity_group': 'B_FIRST_NAME', 'score': 0.99999905, 'word': '', 'start': 32, 'end': 33}
    {'entity_group': 'L_FIRST_NAME', 'score': 0.9999949, 'word': 'MARK', 'start': 32, 'end': 36}
    {'entity_group': 'B_ADDRESS', 'score': 0.9999989, 'word': '123', 'start': 52, 'end': 55}
    {'entity_group': 'I_ADDRESS', 'score': 0.99999917, 'word': 'NORTHSTREETAPT201DESMOINES,IA', 'start': 56, 'end': 91}
    {'entity_group': 'I_DRIVER_LICENSE_NUMBER', 'score': 0.9999995, 'word': '123XX6789', 'start': 118, 'end': 127}
    {'entity_group': 'L_ISSUE_DATE', 'score': 0.99999964, 'word': '1107/2016', 'start': 135, 'end': 144}
    {'entity_group': 'I_EXPIRY_DATE', 'score': 0.99999964, 'word': '01/12/2021', 'start': 152, 'end': 162}
    {'entity_group': 'B_PERSON_NAME', 'score': 0.99999905, 'word': 'Mark', 'start': 234, 'end': 238}
    {'entity_group': 'I_PERSON_NAME', 'score': 0.9999993, 'word': 'Sample', 'start': 239, 'end': 245}
    {'entity_group': 'L_DATE_OF_BIRTH', 'score': 0.99999976, 'word': '01/12/1967', 'start': 301, 'end': 311}

So, given the offset values `entity_group`, `word`, `start`, `end` how can I highlight the original text with the `entity_group` so that it is easy to visulize.


**Final Output**

[![enter image description here][1]][1]




  [1]: https://i.stack.imgur.com/Ef8WB.png

`Is there any python-library that I can use to do it.?`

### Motivation

Makes easy to visualise the NER output

### Your contribution

NA
Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.
Could you ask your question on the [forum](https://discuss.huggingface.co) instead?

Thanks!<|||||>> Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests. Could you ask your question on the [forum](https://discuss.huggingface.co) instead?
> 
> Thanks!

Its a feature request<|||||>Ah, sorry, I misunderstood! In that case, I would say that this is unfortunately out of the scope of the repository. I would look into other utilities to provide color highlighting in outputs<|||||>> Ah, sorry, I misunderstood! In that case, I would say that this is unfortunately out of the scope of the repository. I would look into other utilities to provide color highlighting in outputs

Will it be possible to integrate `Displacy`?<|||||>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.