mark llama4 as not supported with fa2
Author: winglian
Pull request: yes
Labels: name: for patch

# What does this PR do?
While FA2 does "work" with Llama-4, according to @ArthurZucker it still needs kernel support. It's probably best to mark this as not supported otherwise folks might burn cycles wondering why it's not truly converging when training (or inferencing)

For example, using Scout with prefix of `Roses are red,`, the implementations complete these as follows:

- FA2: `['
Roses are red, of the1 in']`
- flex: `['
Roses are red, violets are blue']`

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Fixes # (issue)


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## Who can review?
@ArthurZucker 
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Hi, team. In my case, however I did not meet the generation issue when using flash_attention_2. I load the model via:
```
config = Llama4Config.from_pretrained("meta-llama/Llama-4-Scout-17B-16E-Instruct")
config.text_config._attn_implementation = "flash_attention_2"
model = Llama4ForConditionalGeneration.from_pretrained(
    "meta-llama/Llama-4-Scout-17B-16E-Instruct",
    config=config,
    device_map="auto",
    torch_dtype=torch.bfloat16,
)
```
It does correctly generate `violets are blue` for `Roses are red,`

But I do find the vision attention part does not support flash_attention_2. 

So I wonder what is the root cause of the wrong generation outputs mentioned here? @ArthurZucker @winglian