[Format] Add config lints (#892)

configs/models/internlm/internlm_7b.py

@@ -4,9 +4,9 @@ from opencompass.models import InternLM
 models = [
     dict(
         type=InternLM,
-        path="./internData/",
+        path='./internData/',
         tokenizer_path='./internData/V7.model',
-        model_config="./internData/model_config.py",
+        model_config='./internData/model_config.py',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/judge_llm/auto_j/hf_autoj_bilingual_6b.py

 from opencompass.models import HuggingFaceCausalLM
 
 '''
-This is a bilingual 6B version of Auto-J. 
-It is trained on both the original training data 
-and its Chinese translation, which can be find in 
+This is a bilingual 6B version of Auto-J.
+It is trained on both the original training data
+and its Chinese translation, which can be find in
 https://huggingface.co/GAIR/autoj-bilingual-6b
 '''
 
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='autoj-bilingual-6b',
-        path="GAIR/autoj-bilingual-6b",
+        path='GAIR/autoj-bilingual-6b',
         tokenizer_path='GAIR/autoj-bilingual-6b',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',

configs/models/judge_llm/auto_j/hf_autoj_eng_13b.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='autoj-13b',
-        path="GAIR/autoj-13b",
+        path='GAIR/autoj-13b',
         tokenizer_path='GAIR/autoj-13b',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/auto_j/hf_autoj_eng_13b_4bit.py

 from opencompass.models import HuggingFaceCausalLM
 
 '''
-#This is a 4bits quantized version of Auto-J by using AutoGPTQ, 
-which is available on huggingface-hub: 
+#This is a 4bits quantized version of Auto-J by using AutoGPTQ,
+which is available on huggingface-hub:
 https://huggingface.co/GAIR/autoj-13b-GPTQ-4bits
 '''
 
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='autoj-13b-GPTQ-4bits',
-        path="GAIR/autoj-13b-GPTQ-4bits",
+        path='GAIR/autoj-13b-GPTQ-4bits',
         tokenizer_path='GAIR/autoj-13b-GPTQ-4bits',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -20,4 +20,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/auto_j/hf_autoj_scen_classifier.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='autoj-scenario-classifier',
-        path="GAIR/autoj-scenario-classifier",
+        path='GAIR/autoj-scenario-classifier',
         tokenizer_path='GAIR/autoj-scenario-classifier',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/judgelm/hf_judgelm_13b_v1.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='judgelm-13b-v1-hf',
-        path="BAAI/JudgeLM-13B-v1.0",
+        path='BAAI/JudgeLM-13B-v1.0',
         tokenizer_path='BAAI/JudgeLM-13B-v1.0',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/judgelm/hf_judgelm_33b_v1.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='judgelm-33b-v1-hf',
-        path="BAAI/JudgeLM-33B-v1.0",
+        path='BAAI/JudgeLM-33B-v1.0',
         tokenizer_path='BAAI/JudgeLM-33B-v1.0',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=4, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/judgelm/hf_judgelm_7b_v1.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='judgelm-7b-v1-hf',
-        path="BAAI/JudgeLM-7B-v1.0",
+        path='BAAI/JudgeLM-7B-v1.0',
         tokenizer_path='BAAI/JudgeLM-7B-v1.0',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/pandalm/hf_alpaca_pandalm_7b_v1.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='alpaca-pandalm-7b-v1-hf',
-        path="WeOpenML/PandaLM-Alpaca-7B-v1",
+        path='WeOpenML/PandaLM-Alpaca-7B-v1',
         tokenizer_path='WeOpenML/PandaLM-Alpaca-7B-v1',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/judge_llm/pandalm/hf_pandalm_7b_v1.py

@@ -4,7 +4,7 @@ from opencompass.models import HuggingFaceCausalLM
 models = [dict(
         type=HuggingFaceCausalLM,
         abbr='pandalm-7b-v1-hf',
-        path="WeOpenML/PandaLM-7B-v1",
+        path='WeOpenML/PandaLM-7B-v1',
         tokenizer_path='WeOpenML/PandaLM-7B-v1',
         tokenizer_kwargs=dict(padding_side='left',
                               truncation_side='left',
@@ -15,4 +15,4 @@ models = [dict(
         batch_size=8,
         model_kwargs=dict(device_map='auto', trust_remote_code=True),
         run_cfg=dict(num_gpus=1, num_procs=1),
-    )]
+    )]
\ No newline at end of file

configs/models/lemur/lemur_70b_chat.py

@@ -3,8 +3,8 @@ from opencompass.models import HuggingFaceCausalLM
 
 _meta_template = dict(
     round=[
-        dict(role="HUMAN", begin='\n<|im_start|>user\n', end='<|im_end|>'),
-        dict(role="BOT", begin="\n<|im_start|>assistant\n", end='<|im_end|>', generate=True),
+        dict(role='HUMAN', begin='\n<|im_start|>user\n', end='<|im_end|>'),
+        dict(role='BOT', begin='\n<|im_start|>assistant\n', end='<|im_end|>', generate=True),
     ],
 )
 
@@ -12,7 +12,7 @@ models = [
     dict(
         type=HuggingFaceCausalLM,
         abbr='lemur-70b-chat-v1',
-        path="OpenLemur/lemur-70b-chat-v1",
+        path='OpenLemur/lemur-70b-chat-v1',
         tokenizer_path='OpenLemur/lemur-70b-chat-v1',
         # tokenizer_kwargs=dict(
         #     padding_side='left',

configs/models/llama/llama2_13b.py

@@ -11,10 +11,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-2-13b",
+        abbr='llama-2-13b',
         type=Llama2,
-        path="./models/llama2/llama/llama-2-13b/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-13b/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/llama/llama2_13b_chat.py

@@ -11,17 +11,17 @@ from opencompass.models import Llama2Chat
 
 api_meta_template = dict(
     round=[
-        dict(role="HUMAN", api_role="HUMAN"),
-        dict(role="BOT", api_role="BOT", generate=True),
+        dict(role='HUMAN', api_role='HUMAN'),
+        dict(role='BOT', api_role='BOT', generate=True),
     ],
 )
 
 models = [
     dict(
-        abbr="llama-2-13b-chat",
+        abbr='llama-2-13b-chat',
         type=Llama2Chat,
-        path="./models/llama2/llama/llama-2-13b-chat/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-13b-chat/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         meta_template=api_meta_template,
         max_out_len=100,
         max_seq_len=2048,

configs/models/llama/llama2_70b.py

@@ -11,10 +11,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-2-70b",
+        abbr='llama-2-70b',
         type=Llama2,
-        path="./models/llama2/llama/llama-2-70b/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-70b/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/llama/llama2_70b_chat.py

@@ -11,17 +11,17 @@ from opencompass.models import Llama2Chat
 
 api_meta_template = dict(
     round=[
-        dict(role="HUMAN", api_role="HUMAN"),
-        dict(role="BOT", api_role="BOT", generate=True),
+        dict(role='HUMAN', api_role='HUMAN'),
+        dict(role='BOT', api_role='BOT', generate=True),
     ],
 )
 
 models = [
     dict(
-        abbr="llama-2-70b-chat",
+        abbr='llama-2-70b-chat',
         type=Llama2Chat,
-        path="./models/llama2/llama/llama-2-70b-chat/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-70b-chat/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         meta_template=api_meta_template,
         max_out_len=100,
         max_seq_len=2048,

configs/models/llama/llama2_7b.py

@@ -11,10 +11,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-2-7b",
+        abbr='llama-2-7b',
         type=Llama2,
-        path="./models/llama2/llama/llama-2-7b/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-7b/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/llama/llama2_7b_chat.py

@@ -11,17 +11,17 @@ from opencompass.models import Llama2Chat
 
 api_meta_template = dict(
     round=[
-        dict(role="HUMAN", api_role="HUMAN"),
-        dict(role="BOT", api_role="BOT", generate=True),
+        dict(role='HUMAN', api_role='HUMAN'),
+        dict(role='BOT', api_role='BOT', generate=True),
     ],
 )
 
 models = [
     dict(
-        abbr="llama-2-7b-chat",
+        abbr='llama-2-7b-chat',
         type=Llama2Chat,
-        path="./models/llama2/llama/llama-2-7b-chat/",
-        tokenizer_path="./models/llama2/llama/tokenizer.model",
+        path='./models/llama2/llama/llama-2-7b-chat/',
+        tokenizer_path='./models/llama2/llama/tokenizer.model',
         meta_template=api_meta_template,
         max_out_len=100,
         max_seq_len=2048,

configs/models/llama/llama_13b.py

@@ -12,10 +12,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-13b",
+        abbr='llama-13b',
         type=Llama2,
-        path="./models/llama/13B/",
-        tokenizer_path="./models/llama/tokenizer.model",
+        path='./models/llama/13B/',
+        tokenizer_path='./models/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/llama/llama_30b.py

@@ -12,10 +12,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-30b",
+        abbr='llama-30b',
         type=Llama2,
-        path="./models/llama/30B/",
-        tokenizer_path="./models/llama/tokenizer.model",
+        path='./models/llama/30B/',
+        tokenizer_path='./models/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,

configs/models/llama/llama_65b.py

@@ -12,10 +12,10 @@ from opencompass.models import Llama2
 
 models = [
     dict(
-        abbr="llama-65b",
+        abbr='llama-65b',
         type=Llama2,
-        path="./models/llama/65B/",
-        tokenizer_path="./models/llama/tokenizer.model",
+        path='./models/llama/65B/',
+        tokenizer_path='./models/llama/tokenizer.model',
         max_out_len=100,
         max_seq_len=2048,
         batch_size=16,