Create example code problem fixed
Author: Diksha-Binary-Ninja
Pull request: yes

The error you're encountering is due to the fact that the model you're using, "amazon/MistralLite," doesn't support Flash Attention 2.0. Flash Attention 2.0 is a specific type of attention mechanism, and not all models in the Transformers library are compatible with it.

To resolve this issue, you have a few options:

Use a Different Model: If you specifically need to use Flash Attention 2.0, you'll need to choose a different model that supports it. You can search for models in the Transformers library that are explicitly designed with Flash Attention 2.0, or check for updates to the "amazon/MistralLite" model that may include support for it in the future.

Disable Flash Attention 2.0: If Flash Attention 2.0 is not a strict requirement for your task, you can disable it by removing the use_flash_attention_2=True parameter when loading the model. You can simply use the model like this:  model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto") This way, you'll use the model with its default attention mechanism.

Request Support: As the error message suggests, you can consider opening an issue on GitHub to request support for Flash Attention 2.0 in the "amazon/MistralLite" model. This may not provide an immediate solution but could help in the long run. Choose the option that best fits your needs and requirements for your project. If Flash Attention 2.0 is not crucial for your task, option 2 (disabling it) is the quickest way to proceed without modifying the model itself.

# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

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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