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gyung/lfm25-agentic-hardcase-lora-20260619-v1
lfm25-agentic-hardcase-lora-20260619-v1 is a machine learning model from gyung. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
This public artifact is part of the ko-law-retriever work. It is intended for Korean legal retrieval, evidence selection, or related tool-use experiments.
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From the Hugging Face model README
This public artifact is part of the ko-law-retriever work. It is intended for
Korean legal retrieval, evidence selection, or related tool-use experiments.
Install:
pip install -U "huggingface_hub[cli]" peft transformers
Download:
hf download gyung/lfm25-agentic-hardcase-lora-20260619-v1 --local-dir lfm25-agentic-hardcase-lora-20260619-v1
For LoRA adapters, load with the matching base model:
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_id = "LiquidAI/LFM2.5-8B-A1B"
adapter_id = "gyung/lfm25-agentic-hardcase-lora-20260619-v1"
tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
base_id,
device_map="auto",
torch_dtype="auto",
trust_remote_code=True,
)
model = PeftModel.from_pretrained(model, adapter_id)
For vLLM LoRA serving:
python -m vllm.entrypoints.openai.api_server \
--model LiquidAI/LFM2.5-8B-A1B \
--enable-lora \
--lora-modules lfm25-agentic-hardcase-lora-20260619-v1=./lfm25-agentic-hardcase-lora-20260619-v1 \
--served-model-name lfm25-agentic-hardcase-lora-20260619-v1 \
--max-model-len 12288
gyung/ko-law-retrievergyung/ko-law-retriever-artifacts-20260622