| from mmengine.config import read_base | |
| from opencompass.partitioners import SizePartitioner | |
| from opencompass.runners import LocalRunner | |
| from opencompass.tasks import OpenICLInferTask | |
| from opencompass.models import OpenAI, HuggingFaceCausalLM | |
| from opencompass.models.lagent import CodeAgent | |
| with read_base(): | |
| from .datasets.math.math_gen_943d32 import math_datasets | |
| from .datasets.gsm8k.gsm8k_gen_57b0b1 import gsm8k_datasets | |
| datasets = [] | |
| datasets += gsm8k_datasets | |
| datasets += math_datasets | |
| models = [ | |
| dict( | |
| abbr='gpt-3.5-react', | |
| type=CodeAgent, | |
| llm=dict( | |
| type=OpenAI, | |
| path='gpt-3.5-turbo', | |
| key='ENV', | |
| query_per_second=1, | |
| max_seq_len=4096, | |
| ), | |
| batch_size=8), | |
| dict( | |
| abbr='WizardCoder-Python-13B-V1.0-react', | |
| type=CodeAgent, | |
| llm=dict( | |
| type=HuggingFaceCausalLM, | |
| path="WizardLM/WizardCoder-Python-13B-V1.0", | |
| tokenizer_path='WizardLM/WizardCoder-Python-13B-V1.0', | |
| tokenizer_kwargs=dict( | |
| padding_side='left', | |
| truncation_side='left', | |
| trust_remote_code=True, | |
| ), | |
| max_seq_len=2048, | |
| model_kwargs=dict(trust_remote_code=True, device_map='auto'), | |
| ), | |
| batch_size=8, | |
| run_cfg=dict(num_gpus=2, num_procs=1)), | |
| ] | |
| infer = dict( | |
| partitioner=dict(type=SizePartitioner, max_task_size=40000), | |
| runner=dict( | |
| type=LocalRunner, max_num_workers=16, | |
| task=dict(type=OpenICLInferTask)), | |
| ) | |