Refactor Cohere Model
Author: saurabhdash2512
Pull request: yes

# What does this PR do?

Refactor Cohere Model

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Fixes # (issue)


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## Who can review?

 @ArthurZucker and @younesbelkada

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
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Models:

- text models: @ArthurZucker and @younesbelkada
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @gante
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @pacman100

Integrations:

- deepspeed: HF Trainer/Accelerate: @pacman100
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc and @younesbelkada

Documentation: @stevhliu and @MKhalusova

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

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Comments:
As a followup, adding integration tests for the new model will be nice. 

I think there's an issue with the tokenizer.json (or the way transformers is converting). Random multilingual out of nowhere.

See: https://huggingface.co/CohereForAI/c4ai-command-r-plus/discussions/15

Found this after converting to mlx-lm, but was found to be reproducible via the following:

You can reproduce with:

```from transformers import AutoTokenizer
 
tokenizer = AutoTokenizer.from_pretrained("CohereForAI/c4ai-command-r-plus")
tokenizer.save_pretrained(".")```

Concretely, loading -> saving -> loading the tokenizer all through HF `AutoTokenizer` produces a new tokenizer than the initial loaded one with worse behavior. Presumably that should not be the case.

worth noting - the bitsandbytes 4 bit repo linked from the main cohere repo is also a different size and looks very different from the original model repo's tokenizer.json (https://huggingface.co/CohereForAI/c4ai-command-r-plus-4bit/blob/main/tokenizer.json).

another interesting difference between the 4 bit bnb tokenizer and the original - in the original one, token id token id 255001 
, special is set to False. In the 4bit bnb one, it's True.

I have no idea what you are talking about? A 4bit tokenizer? could you actually open an issue with a repro and the issue?

I think the difference between two tokenizers.json is unicode encoding after `tokenizer.save_pretrained` which is used to save tokenizer in 4bit model. Also, in the config 
 token is also set as special because it is used as eos_token, which is also overwritten in the original tokenizer (command-r-plus) as well. Therefore, two tokenizers should work the same. @fblissjr it would be helpful if you post the text you tokenize to double-check and reproduce. 

> I have no idea what you are talking about? A 4bit tokenizer? could you actually open an issue with a repro and the issue?

What @ahmetustun mentioned is the difference - not a 4 bit tokenizer, the tokenizer.json in https://huggingface.co/CohereForAI/c4ai-command-r-plus vs. https://huggingface.co/CohereForAI/c4ai-command-r-plus-4bit, which @ahmetustun clarified.

Not at my workstation now, but if nobody else is seeing this issue, I'll assume I've got something wrong on my end. Thanks for the clarification.



Please left further comment in the model repo if the problem continues. Thanks @fblissjr.