Repository: open-compass/opencompass
Issue: [Bug] run pytorch Qwen-7B-Chat with ARC-c ppl under CPU ,and result is not good
Root cause: Environment Incompatibility

### Prerequisite

- [x] I have searched [Issues](https://github.com/open-compass/opencompass/issues/) and [Discussions](https://github.com/open-compass/opencompass/discussions) but cannot get the expected help.
- [X] The bug has not been fixed in the [latest version](https://github.com/open-compass/opencompass).

### Type

I'm evaluating with the officially supported tasks/models/datasets.

### Environment

opencompass recommend conda env


### Reproduces the problem - code/configuration sample

--datasets arc_c_ppl --hf-path /home/test/llm_mode_debug/qwen7_B/ --tokenizer-path /home/test/llm_mode_debug/qwen7_B/  --tokenizer-kwargs padding_side='left' truncation='left' trust_remote_code=True --model-kwargs trust_remote_code=True device_map='cpu' --max-seq-len 2048 --max-out-len 16 --batch-size 1 --num-gpus 0 --debug

### Reproduces the problem - command or script

--datasets arc_c_ppl --hf-path /home/test/llm_mode_debug/qwen7_B/ --tokenizer-path /home/test/llm_mode_debug/qwen7_B/  --tokenizer-kwargs padding_side='left' truncation='left' trust_remote_code=True --model-kwargs trust_remote_code=True device_map='cpu' --max-seq-len 2048 --max-out-len 16 --batch-size 1 --num-gpus 0 --debug

### Reproduces the problem - error message

Loading checkpoint shards: 100%|██████████| 8/8 [00:05<00:00,  1.35it/s]
06/03 17:29:13 - OpenCompass - INFO - Start inferencing [opencompass.models.huggingface.HuggingFace_llm_mode_debug_qwen7_B/ARC-c]
[2024-06-03 17:29:33,307] [opencompass.openicl.icl_inferencer.icl_ppl_inferencer] [INFO] Calculating PPL for prompts labeled 'A'
100%|██████████| 295/295 [8:32:09<00:00, 104.17s/it]
[2024-06-04 09:41:03,213] [opencompass.openicl.icl_inferencer.icl_ppl_inferencer] [INFO] Calculating PPL for prompts labeled 'B'
100%|██████████| 295/295 [8:31:23<00:00, 104.01s/it]
[2024-06-04 18:12:26,649] [opencompass.openicl.icl_inferencer.icl_ppl_inferencer] [INFO] Calculating PPL for prompts labeled 'C'
100%|██████████| 295/295 [8:36:10<00:00, 104.99s/it]
[2024-06-05 02:48:37,632] [opencompass.openicl.icl_inferencer.icl_ppl_inferencer] [INFO] Calculating PPL for prompts labeled 'D'
100%|██████████| 295/295 [8:42:03<00:00, 106.18s/it]
06/05 11:34:31 - OpenCompass - INFO - Partitioned into 1 tasks.
06/05 11:34:33 - OpenCompass - INFO - Task [opencompass.models.huggingface.HuggingFace_llm_mode_debug_qwen7_B/ARC-c]: {'accuracy': 35.25423728813559}
dataset    version    metric    mode      opencompass.models.huggingface.HuggingFace_llm_mode_debug_qwen7_B
---------  ---------  --------  ------  -------------------------------------------------------------------
ARC-c      a450bd     accuracy  ppl                                                                   35.25

### Other information

_No response_

We haven't verify the results on CPU.

> We haven't verify the results on CPU.

Thanks, here is another question,Just feel confuse for the evalution resut ,Take arc-c  for an example, https://hub.opencompass.org.cn/dataset-detail/ARC-c , I saw the official result from opencompass, I could saw some detail for the dataset link, but seems hard for me to judge data from gen or ppl method.
 [官网](https://allenai.org/data/arc)
[GitHub](https://allenai.org/data/arc)
[论文/技术报告](https://arxiv.org/pdf/1803.05457.pdf)

How do I distinguish the result test from GEN or PPL, I got the result both ppl and gen from opencompass test. Please kindly correct me if I was wrong. Thanks 


@tonysy Could you please kindly help to review my question?  take https://hub.opencompass.org.cn/dataset-detail/ARC-c  for example, is the data from gen or ppl test, the result provide base on which gpu?