add more model into benchmark and evaluate workflow

[zhulinJulia24]

1. make evaluate dataset as an input in workflow; add more models into evaluation regression
2. react evaluate config to make it easy to maintain. Add llama3、qwen1.5 moe、kvint4 config for evaluate regression.
3. add more models into benchmark and modify max batch size in benchmark.
4. add more support models and remove some old models in regression test.

benchmark test record: https://github.com/zhulinJulia24/lmdeploy/actions/runs/8998731504
evaluation test record: https://github.com/zhulinJulia24/lmdeploy/actions/runs/9012663244

[zhulinJulia24]

https://github.com/zhulinJulia24/lmdeploy/actions/runs/9015990252 this contains all without qwen moe

[lvhan028]

The more datasets involves, the more time the evaluation costs.
I suggest keeping eval, gsm8k and mmlu, and remove the rest.

[zhulinJulia24]

The more datasets involves, the more time the evaluation costs. I suggest keeping eval, gsm8k and mmlu, and remove the rest.

yes. Default datasets is gsm8k and mmlu controlled by workflow input. If I want to evaluate more datesets, I can also use the same workflow with different input. the value is here https://github.com/zhulinJulia24/lmdeploy/blob/497783134da77790096a2a25f10244aa11cef134/.github/workflows/evaluate.yml#L25

[RunningLeon]

LGTM