1from peft import PeftModel
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4base_id = "LiquidAI/LFM2.5-8B-A1B"
5adapter_id = "gyung/lfm25-agentic-hardcase-lora-20260619-v1"
6
7tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
8model = AutoModelForCausalLM.from_pretrained(
9 base_id,
10 device_map="auto",
11 torch_dtype="auto",
12 trust_remote_code=True,
13)
14model = PeftModel.from_pretrained(model, adapter_id)
1python -m vllm.entrypoints.openai.api_server \
2 --model LiquidAI/LFM2.5-8B-A1B \
3 --enable-lora \
4 --lora-modules lfm25-agentic-hardcase-lora-20260619-v1=./lfm25-agentic-hardcase-lora-20260619-v1 \
5 --served-model-name lfm25-agentic-hardcase-lora-20260619-v1 \
6 --max-model-len 12288