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ReMe/benchmark/halumem/quickstart.md
方应 89a86839a3 docs(benchmark): add quick start guides for halumem and longmemeval experiments 
- Created HaluMem experiment quick start guide with ReMe integration setup
- Added detailed steps for installing ReMe environment using conda
- Included repository cloning instructions for HaluMem benchmark
- Provided complete command examples for running HaluMem experiments
- Created LongMeMEval quick start guide with data download procedures
- Added wget commands for downloading cleaned dataset files
- Included evaluation script instructions for computing experiment statistics
- Documented parameter configurations for different model types and batch sizes
2026-03-31 20:27:48 +08:00

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Halumem

Experiment Quick Start Guide This guide helps you quickly set up and run Halumem experiments with ReMe integration.

1. Start ReMe Service

Install ReMe (if not already installed) If you haven't installed the ReMe environment yet, follow these steps:

# Create ReMe environment
conda create -p ./reme-env python==3.12
conda activate ./reme-env

# Install ReMe
pip install .

2. Clone the Repository

cd ./benchmark/halumem
git clone https://github.com/MemTensor/HaluMem.git

3. Run Experiments

Launch the ReMe service to enable memory library functionality:

clear && python benchmark/halumem/eval_reme.py \
    --data_path benchmark/halumem/HaluMem/data/HaluMem-Medium.jsonl \
    --reme_model_name gpt-4o-mini-2024-07-18 \
    --eval_model_name gpt-4o-mini-2024-07-18 \
    --batch_size 40 \
    --algo_version default