File size: 3,237 Bytes
256a159 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
from mmengine.config import read_base
from opencompass.models.turbomind import TurboMindModel
with read_base():
# choose a list of datasets
from .datasets.mmlu.mmlu_gen_a484b3 import mmlu_datasets
from .datasets.ceval.ceval_gen_5f30c7 import ceval_datasets
from .datasets.SuperGLUE_WiC.SuperGLUE_WiC_gen_d06864 import WiC_datasets
from .datasets.SuperGLUE_WSC.SuperGLUE_WSC_gen_7902a7 import WSC_datasets
from .datasets.triviaqa.triviaqa_gen_2121ce import triviaqa_datasets
from .datasets.gsm8k.gsm8k_gen_1d7fe4 import gsm8k_datasets
from .datasets.race.race_gen_69ee4f import race_datasets
from .datasets.crowspairs.crowspairs_gen_381af0 import crowspairs_datasets
# and output the results in a choosen format
from .summarizers.medium import summarizer
datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])
internlm_meta_template = dict(round=[
dict(role='HUMAN', begin='<|User|>:', end='\n'),
dict(role='BOT', begin='<|Bot|>:', end='<eoa>\n', generate=True),
],
eos_token_id=103028)
internlm2_meta_template = dict(
round=[
dict(role='HUMAN', begin='<|im_start|>user\n', end='<|im_end|>\n'),
dict(role='BOT', begin='<|im_start|>assistant\n', end='<|im_end|>\n', generate=True),
],
eos_token_id=92542
)
# config for internlm-chat-7b
internlm_chat_7b = dict(
type=TurboMindModel,
abbr='internlm-chat-7b-turbomind',
path='internlm/internlm-chat-7b',
engine_config=dict(session_len=2048,
max_batch_size=32,
rope_scaling_factor=1.0),
gen_config=dict(top_k=1,
top_p=0.8,
temperature=1.0,
max_new_tokens=100),
max_out_len=100,
max_seq_len=2048,
batch_size=32,
concurrency=32,
meta_template=internlm_meta_template,
run_cfg=dict(num_gpus=1, num_procs=1),
end_str='<eoa>',
)
# config for internlm-chat-7b
internlm2_chat_7b = dict(
type=TurboMindModel,
abbr='internlm2-chat-7b-turbomind',
path='internlm/internlm2-chat-7b',
engine_config=dict(session_len=2048,
max_batch_size=32,
rope_scaling_factor=1.0),
gen_config=dict(top_k=1,
top_p=0.8,
temperature=1.0,
max_new_tokens=100),
max_out_len=100,
max_seq_len=2048,
batch_size=32,
concurrency=32,
meta_template=internlm2_meta_template,
run_cfg=dict(num_gpus=1, num_procs=1),
end_str='<|im_end|>'
)
# config for internlm-chat-20b
internlm_chat_20b = dict(
type=TurboMindModel,
abbr='internlm-chat-20b-turbomind',
path='internlm/internlm-chat-20b',
engine_config=dict(session_len=2048,
max_batch_size=8,
rope_scaling_factor=1.0),
gen_config=dict(top_k=1,
top_p=0.8,
temperature=1.0,
max_new_tokens=100),
max_out_len=100,
max_seq_len=2048,
batch_size=8,
concurrency=8,
meta_template=internlm_meta_template,
run_cfg=dict(num_gpus=1, num_procs=1),
end_str='<eoa>',
)
models = [internlm_chat_20b]
|