burn inference and training of dragon hatchling model
- cached inference
- training benchmarks and reporting
- pope positional embeddings
- wasm deployments
- adaptive tool discovery
- conditional (deep) gating
- document-coherent dataloading and scale mixup
- episodic memory
- fused kernels
- hierarchical, memory-aware recurrent state
- mixture-of-expert routing
- multi-modal architecture
- multi-stream truncated backpropagation through time
- neuromorphic backend
- rl reasoning training
- sparsity metrics and visualization
- streaming, sparse synaptic backpropagation
- temporal neuron dampening
Dataset configuration (built-in presets and Hugging Face examples) is documented inline in config/base.toml.
cargo run --release(defaults to the cuda backend)
cargo run --bin infer -- --max-tokens 2048 --streaming
cargo bench(executes both wgpu and cuda benchmarks)- open
target/criterion/report/index.html
burn_dragon_hatchling |
burn |
|---|---|
0.2 |
0.19 |
0.1 |
0.18 |
licensed under either of
- Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (http://opensource.org/licenses/MIT)
at your option.
unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
