doc-to-lora/tmp/test_llm_lingua.py
2025-09-29 00:40:51 +09:00

19 lines
613 B
Python

from llmlingua import PromptCompressor
with open("src/ctx_to_lora/modeling/test_ctx.txt") as f:
prompt = f.read()
llm_lingua = PromptCompressor(
model_name="microsoft/llmlingua-2-xlm-roberta-large-meetingbank",
use_llmlingua2=True, # Whether to use llmlingua-2
)
compressed_prompt = llm_lingua.compress_prompt(
prompt, rate=0.25, force_tokens=["\n", "?"]
)
print(compressed_prompt)
## Or use LLMLingua-2-small model
# llm_lingua = PromptCompressor(
# model_name="microsoft/llmlingua-2-bert-base-multilingual-cased-meetingbank",
# use_llmlingua2=True, # Whether to use llmlingua-2
# )