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64adc1166c
- Replace repository cloning with direct dataset download using curl - Add commands to download HaluMem-Medium.jsonl and HaluMem-Long.jsonl files - Include both official Hugging Face and mirror download sources - Update data path reference from nested directory to local data folder - Add dataset page link and mirror usage instructions for mainland China access
46 lines
1.6 KiB
Markdown
46 lines
1.6 KiB
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. Download the Dataset
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```bash
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cd ./benchmark/halumem
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mkdir -p data
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curl -L "https://huggingface.co/datasets/IAAR-Shanghai/HaluMem/resolve/main/HaluMem-Medium.jsonl?download=true" -o data/HaluMem-Medium.jsonl
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curl -L "https://huggingface.co/datasets/IAAR-Shanghai/HaluMem/resolve/main/HaluMem-Long.jsonl?download=true" -o data/HaluMem-Long.jsonl
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```
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Dataset page:
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https://huggingface.co/datasets/IAAR-Shanghai/HaluMem/tree/main
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If the official source is slow or inaccessible in mainland China, you can use a mirror:
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```bash
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cd ./benchmark/halumem
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mkdir -p data
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curl -L "https://hf-mirror.com/datasets/IAAR-Shanghai/HaluMem/resolve/main/HaluMem-Medium.jsonl?download=true" -o data/HaluMem-Medium.jsonl
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curl -L "https://hf-mirror.com/datasets/IAAR-Shanghai/HaluMem/resolve/main/HaluMem-Long.jsonl?download=true" -o data/HaluMem-Long.jsonl
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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/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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