Deploying LLMs offline on the NVIDIA Jetson platform marks the dawn of a new era in embodied intelligence, where devices can function independently without continuous internet access.
This project focuses on adapting LMDeploy for use with NVIDIA Jetson series edge computing cards, facilitating the implementation of InternLM series LLMs for Offline Embodied Intelligence (OEI).
- [2024/3/15] Updated suppoort for LMDeploy-v0.2.5.
- [2024/2/26] This project has been included in the LMDeploy community.
- Recruiting community managers (Contact: [email protected])
- Recruiting benchmark testing data for more models of Jetson boards (please PR directly), such as:
- Jetson Nano
- Jetson TX2
- Jetson AGX Xavier
- Jetson Orin Nano
- Jetson AGX Orin
- Recruiting developers to create Jetson-specific whl distributions
- README optimization, etc.
- ✅:Verified and runnable
- ❌:Verified but not runnable
- ⭕️:Pending verification
Models | InternLM-7B | InternLM-20B | InternLM2-1.8B | InternLM2-7B | InternLM2-20B |
---|---|---|---|---|---|
Orin AGX(32G) Jetpack 5.1 |
✅ Mem:??/?? 14.68 token/s |
✅ Mem:??/?? 5.82 token/s |
✅ Mem:??/?? 56.57 token/s |
✅ Mem:??/?? 14.56 token/s |
✅ Mem:??/?? 6.16 token/s |
Orin NX(16G) Jetpack 5.1 |
✅ Mem:8.6G/16G 7.39 token/s |
✅ Mem:14.7G/16G 3.08 token/s |
✅ Mem:5.6G/16G 22.96 token/s |
✅ Mem:9.2G/16G 7.48 token/s |
✅ Mem:14.8G/16G 3.19 token/s |
Xavier NX(8G) Jetpack 5.1 |
❌ | ❌ | ✅ Mem:4.35G/8G 28.36 token/s |
❌ | ❌ |
If you have more Jetson series boards, feel free to run benchmarks and submit the results via Pull Requests
(PR) to become one of the community contributors!
- Updating benchmark testing data for more models of Jetson boards.
- Creating Jetson-specific whl distributions.
- Following up on updates to the LMDeploy version.
S1.Quantize on server by W4A16
S2.Install Miniconda on Jetson
S3.Install CMake-3.29.0 on Jetson
S4.Install RapidJson on Jetson
S5.Install Pytorch-2.1.0 on Jetson
S6.Port LMDeploy-0.2.5 to Jetson
S7.Run InternLM offline on Jetson
- InternDog: Offline embodied intelligent guide dog based on the InternLM2. [Github] [Bilibili]
If this project is helpful to your work, please cite it using the following format:
@misc{2024lmdeployjetson,
title={LMDeploy-Jetson:Opening a new era of Offline Embodied Intelligence},
author={LMDeploy-Jetson Community},
url={https://github.com/BestAnHongjun/LMDeploy-Jetson},
year={2024}
}