burn-lm-cli
| Crates.io | burn-lm-cli |
| lib.rs | burn-lm-cli |
| version | 0.0.1 |
| created_at | 2025-08-04 19:05:34.276734+00 |
| updated_at | 2025-08-04 19:05:34.276734+00 |
| description | Burn Large Models Engine - CLI. |
| homepage | |
| repository | https://github.com/tracel-ai/burn-lm |
| max_upload_size | |
| id | 1781059 |
| size | 256,305 |
Nathaniel Simard (nathanielsimard)
documentation
README
Burn LM
Burn-LM aims at democratizing large model inference and training on any device.
Quick Start
Launch a Burn LM shell with:
git clone https://github.com/tracel-ai/burn-lm.git
cd burn-lm
cargo burn-lm
Type help to get a list of commands.
Available Models
The list of models is very small at the moment since we're focused on performance optimization. Still, we're accepting high quality contributions to port open-source models to Burn-LM.
Here's the current list of supported models:
| Model | Size |
|---|---|
| Llama 3 | 8B |
| Llama 3.1 | 8B |
| Llama 3.2 | 1B, 3B |
| TinyLlama | 1.1B |
Adding a New Model
Models can be easily integrated with Burn LM by implementing the InferenceServer
trait to create a pluggable server that can be added to the Burn LM registry.
To bootstrap a new model server you can use the dedicated command new:
cargo burn-lm new "my-model"
This will create a new crate named burn-lm-inference-my-model and automatically
register it in burn-lm-registry.
The bootstraped server is a model-less server that just repeat the prompt it is
given. You can also get inspiration from the other crate with the crate burn-lm-llama.