CLI cheat sheet
One-page reference for the most common commands.
Build
cargo build --release --workspace # everything, CPU
cargo build --release -p typed-lm-serve --features mkl # server, CPU + MKL
cargo build --release -p typed-lm-serve --features cuda # server, CUDA
Serve
typed-lm-serve # default model
typed-lm-serve --context-path resources/memory.md # with context
typed-lm-serve --model-id output/quantized # serve an artifact
Ask
curl -s http://127.0.0.1:8080/v1/systemone \
-H 'Content-Type: application/json' \
-d @examples/request_mixed.json
curl -s http://127.0.0.1:8080/v1/models
curl -s http://127.0.0.1:8080/health
curl -s http://127.0.0.1:8080/health/live
Train
# LoRA adapter.
typed-lm-trainer train \
--model-id /path/to/local/checkpoint \
--dataset resources/dataset.jsonl \
--output-directory output/train \
--method lora --epochs 3 --batch-size 4 --learning-rate 1e-4
# From scratch (explicit geometry + tokenizer).
typed-lm-trainer train \
--method from-scratch --architecture qwen2 \
--vocab-size 151936 --hidden-size 512 --intermediate-size 2048 \
--num-hidden-layers 8 --num-attention-heads 8 --num-key-value-heads 4 \
--max-position-embeddings 1024 \
--tokenizer-file /path/to/tokenizer.json \
--dataset resources/dataset.jsonl --output-directory output/scratch \
--seed 42 --epochs 3 --batch-size 4 --learning-rate 1e-4
Quantize
typed-lm-trainer quantize \
--model-id /path/to/local/checkpoint \
--adapter-directory output/train \
--quantization fp8 --output-directory output/quantized
Test
cargo test --workspace # unit + integration
cargo test --workspace -- --ignored --nocapture # live tests (weights)
cargo test -p typed-lm-serve --test end_to_end # train -> quantize -> serve