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OmniJev-4B v1.1 preparation

This recipe prepares OmniJev-4B v1.1 (#114) for the native worker: it exports the checkpoint and regenerates the CPU fixtures that the contract and preparation tests use. The native worker itself is not available yet; the model README describes what is implemented. Run the commands from the repository root.

Reference environment

The export and the fixtures use the reference's own code and Python packages on the CPU; no GPU is needed.

python3.10 -m venv .venv-omnijev
.venv-omnijev/bin/pip install torch==2.14.0 torchvision==0.29.0 transformers==5.17.0 peft==0.19.1 accelerate pillow
git clone https://github.com/tinnel123666888/OmniJev
git -C OmniJev checkout 14dbec4f71e194852c8d7b88ab36ef639493f400

Leave fla-core uninstalled, so transformers runs its PyTorch Gated DeltaNet code. Keep transformers at 5.7.0 or later: older releases do not continue the linear-attention state across the reference's prefix. The fixtures were generated with Python 3.10.12; Python 3.12 changed how sum adds floats, which the reference's calibration uses.

Download the pinned files

hf download tinnel123/OmniJev --revision ffe5f436eaf22e20e2f041f8e74e121fd057a6cb --local-dir omnijev-v1.1
hf download Qwen/Qwen3.5-4B --revision 851bf6e806efd8d0a36b00ddf55e13ccb7b8cd0a --local-dir qwen3.5-4b

Export

.venv-omnijev/bin/python recipe/omnijev/export.py --base qwen3.5-4b --checkpoint omnijev-v1.1 --out omnijev-export

The export checks the checkpoint files it reads against the release's release_manifest.json and the base model's shards, index and config.json against their pinned SHA-256, then writes:

  • the language model in BF16 with the adapter merged, its tied embedding resized to the tokenizer's 248,079 entries and the two option tokens' saved rows restored, and config.json with the vision configuration;
  • vision.safetensors, the base vision tower, which the adapter does not change;
  • heads.safetensors, the decision and ordinal heads in FP32;
  • the tokenizer and chat template;
  • omnijev_export.json, written last, with the revisions, calibration, image budget, and the SHA-256 of the checked inputs and of every output file.

It writes into .<out>.partial next to the output and renames it at the end, so a failed export leaves no output directory; the next run removes the partial one. It needs about 18 GB of host RAM and writes 9 GB; on a 48-core workstation it takes under a minute.

Fixtures and tests

.venv-omnijev/bin/python tests/omnijev/generate_fixtures.py \
    --reference OmniJev --checkpoint omnijev-v1.1 --base qwen3.5-4b --out tests/omnijev/data
cargo test --locked -p omni-omnijev-native
OMNIJEV_CHECKPOINT=$PWD/omnijev-v1.1 OMNIJEV_EXPORT=$PWD/omnijev-export \
    cargo test --locked -p omni-omnijev-native -- --include-ignored

The generator runs the reference's preparation, layout, rotary positions, heads and finishing without loading the backbone. The ordinary tests need only the committed fixtures; the opt-in ones compare token ids with the checkpoint's tokenizer and the heads with the export. Cargo runs the tests from the crate's directory, so the two paths must be absolute.