mirror of
https://github.com/agentscope-ai/ReMe.git
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89a86839a3
- 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
33 lines
876 B
Markdown
33 lines
876 B
Markdown
# Halumem
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Experiment Quick Start Guide
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This guide helps you quickly set up and run Halumem experiments with ReMe integration.
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### 1. Start ReMe Service
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Install ReMe (if not already installed)
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If you haven't installed the ReMe environment yet, follow these steps:
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```bash
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# Create ReMe environment
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conda create -p ./reme-env python==3.12
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conda activate ./reme-env
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# Install ReMe
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pip install .
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```
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### 2. Clone the Repository
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```bash
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cd ./benchmark/halumem
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git clone https://github.com/MemTensor/HaluMem.git
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```
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### 3. Run Experiments
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Launch the ReMe service to enable memory library functionality:
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```bash
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clear && python benchmark/halumem/eval_reme.py \
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--data_path benchmark/halumem/HaluMem/data/HaluMem-Medium.jsonl \
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--reme_model_name gpt-4o-mini-2024-07-18 \
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--eval_model_name gpt-4o-mini-2024-07-18 \
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--batch_size 40 \
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--algo_version default
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```
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