Basic Environmental Requirements
- operating system: Linux/Windows (Ubuntu 20.04+ recommended)
- software dependency: Python 3.8+, Git, PyTorch 2.0+, Transformers Library
- account access: HuggingFace account (for downloading models such as Llama)
Step-by-step installation guide
- Cloning Warehouse:
git clone https://github.com/microsoft/KBLaM.git - Install core dependencies:
pip install -e . - Configure model permissions:
huggingface-cli login(token required) - Verify Installation: Run
python -m kblam.test
Hardware Configuration Recommendations
Small-scale testing: The RTX 3090 (24GB of video memory) can handle 100MB-class knowledge bases;production deployment: The A100 80GB is recommended to handle millions of knowledge entries. Response time may be 5-8 times longer if only CPU computing is used.
This answer comes from the articleKBLaM: An Open Source Enhanced Tool for Embedding External Knowledge in Large ModelsThe
May not be reproduced without permission:AI productivity tools " How do I install and configure the KBLaM environment? What hardware support is required?
