OpenCompass/configs/models/hf_llama/lmdeploy_llama_series.py
2024-05-14 22:42:23 +08:00

31 lines
1.1 KiB
Python

from opencompass.models import TurboMindModel
settings = [
('llama-7b-turbomind', 'huggyllama/llama-7b', 1),
('llama-13b-turbomind', 'huggyllama/llama-13b', 1),
('llama-30b-turbomind', 'huggyllama/llama-30b', 2),
('llama-65b-turbomind', 'huggyllama/llama-65b', 4),
('llama-2-7b-turbomind', 'meta-llama/Llama-2-7b-hf', 1),
('llama-2-13b-turbomind', 'meta-llama/Llama-2-13b-hf', 1),
('llama-2-70b-turbomind', 'meta-llama/Llama-2-70b-hf', 4),
('llama-3-8b-turbomind', 'meta-llama/Meta-Llama-3-8B', 1),
('llama-3-70b-turbomind', 'meta-llama/Meta-Llama-3-70B', 4),
]
models = []
for abbr, path, num_gpus in settings:
models.append(
dict(
type=TurboMindModel,
abbr=abbr,
path=path,
engine_config=dict(session_len=2048, max_batch_size=16, tp=num_gpus),
gen_config=dict(top_k=1, temperature=1, top_p=0.9, max_new_tokens=1024),
max_out_len=1024,
max_seq_len=2048,
batch_size=16,
concurrency=16,
run_cfg=dict(num_gpus=num_gpus),
)
)