[Test] Make model tests run again and remove --forked from pytest

[rkooo567]

This PR makes model_tests work by

1. Right now, some tests fail because fork is called after cuda context is initialized. This is due to the usage of --forked [Bug]: Using pytest --forked when CUDA is not generally fork-safe #3557. The reason why --forked is required is to clean up resources by simply killling processes. This PR removes the usage of --forked from pytest and instead doing clean up using fixtures.
2. Fixed the issue where del hf_model or del vllm_model doesn't actually clean up GPU usage.
3. When running a large model in small GPUs (like the one used in CI) vllm fails to initialize because the machine doesn't have kv cache to match model_len. It uses the smaller model_len by default (1024) to avoid this issue. Note that none of tests require more than 128 tokens to generate.
4. Separate out big models (7B) to different test suites.
5. Skip failed model tests. Also remove soft_fail: true from model tests

The following models fail to succeed.

• allenai/OLMo-1B: TypeError: forward() got an unexpected keyword argument 'cache_position'
• mistralai/Mistral-7B-v0.1: correctness issue (generate doesn't generate any token) + RuntimeError: expected scalar type BFloat16 but found Half (only in CI)
• Deci/DeciLM-7b: correctness issue (output is different)
• tiiuae/falcon-7b: correctness issue (output is different)
  -"Qwen/Qwen1.5-0.5B": Correctness issue

Closes #3557

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[rkooo567]

without this, the global cleanup conftest cleans this up

[simon-mo]

maybe revert this since the comment says the extra del line is needed for different GPUs?

[rkooo567]

it is actually broken because marlin_model.model.llm_engine.driver_worker doesn't exist anymore. I believe what I am doing in __del__ inside vllm runner should do the same thing (and the test seems passing?).

[simon-mo]

can this be more?

[rkooo567]

Trying 128. But these models currently use half precision, so I think having large values here is risky (we should use a bigger machine eventually to resolve it. )

[rkooo567]

Big model tests seem to fail with 128. Let me try 64 and see how it goes

[rkooo567]

32 makes "EleutherAI/gpt-j-6b", pass. "Qwen/Qwen1.5-0.5B" didn't pass on 32 (but passed on 5), so I just skipped it for now

[rkooo567]

@simon-mo addressed all comments!

[cadedaniel]

Thanks for cleaning this up!