burn_dragon 🔥🐉🐣

burn inference and training of the dragon model

features

• cached inference
• training benchmarks and reporting
• pope positional embeddings
• wasm deployments
• sparsity metrics and visualization
• vision dragon cortical column/stack
• recurrent, foveated saccade training and inference
• GDPO
• 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
• streaming, sparse synaptic backpropagation
• temporal neuron dampening

Dataset configuration (built-in presets and Hugging Face examples) is documented inline in config/language/base.toml.

training

• cargo run -p burn_dragon_cli --release (defaults to the cuda backend)

inference

• cargo run -p burn_dragon_cli --bin infer -- --max-tokens 2048 --streaming

benchmarks

• cargo bench -p burn_dragon --features train,benchmark (executes both wgpu and cuda benchmarks)
• open target/criterion/report/index.html

compatible burn versions

license

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.

contribution

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.