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Install

DocumentLanguageModel is a Python package. It depends on torch (GPU or CPU build), transformers, peft, trl, and — optionally for export — the ollama binary on your PATH.

Prerequisites

Requirement Minimum Notes
Python 3.11 pyproject.toml pins python >= 3.11.
uv any recent Used for dependency resolution and running scripts.
PyTorch 2.4+ Installed automatically by uv sync.
Ollama as reported by dlm doctor Only needed for dlm export smoke runs.
vendor/llama.cpp submodule built Only needed for dlm export. scripts/bump-llama-cpp.sh build compiles llama-quantize + llama-imatrix.

On Apple Silicon, MPS acceleration is detected automatically and DLM plans for fp16 LoRA. On CUDA, compute capability ≥ 8.0 (Ampere and newer) unlocks bf16 + QLoRA 4-bit. See Architecture for the full refusal matrix.

Install from source

git clone https://github.com/tenseleyFlow/DocumentLanguageModel.git
cd DocumentLanguageModel
uv sync
uv run dlm --help

uv sync resolves the dependency tree into .venv/ and pulls the pinned versions from uv.lock. Use uv run dlm <command> (not dlm <command> — the CLI isn't on your shell PATH unless you activate the venv).

Install from PyPI

# Coming with v1.0 — the tagged release workflow publishes to PyPI via
# trusted-publisher OIDC. Until then, install from source.
pip install dlm

Verify

$ uv run dlm --version
dlm 0.1.0

$ uv run dlm doctor
backend: mps
precision: fp16
attn:     sdpa
...

dlm doctor is the first command to run on a new machine. It probes the GPU, reports the memory budget, picks a training plan, and warns about anything missing (e.g. FlashAttention unavailable, bitsandbytes not importable on CPU-only hosts).

Next

Got dlm doctor output that looks healthy? Move on to the first training cycle.