| --- |
| license: apache-2.0 |
| tags: |
| - vllm-omni |
| - audiox |
| - test-fixture |
| --- |
| |
| # AudioX random / test fixture |
|
|
| A tiny **random-init** bundle of [vLLM-Omni](https://github.com/vllm-project/vllm-omni)'s |
| `AudioXPipeline`. Used by the L1/L2 `core_model` CI tests |
| (`tests/e2e/offline_inference/test_audiox_model.py`, |
| `tests/e2e/online_serving/test_audiox_online.py`) so they can verify the full |
| pipeline (load → forward → trim → return numpy WAV) end-to-end without paying |
| the cost of the real ~11 GB checkpoint. |
|
|
| It follows the same `config.json` schema as |
| [`zhangj1an/AudioX`](https://huggingface.co/zhangj1an/AudioX), but with much |
| smaller transformer dimensions: |
|
|
| - `embed_dim`: 1536 → 384 |
| - `depth`: 24 → 4 |
| - `num_heads`: 24 → 6 |
| - `gate_type_config.num_experts_per_modality`: 64 → 16 |
| - `gate_type_config.num_fusion_layers`: 8 → 2 |
| - `sample_size`: 485100 → 483328 (still gives `latent_len = sample_size // 2048 = 236`, |
| matching the transformer's RoPE precompute) |
|
|
| All weights are random, fp16, generated by running the `AudioXPipeline.__init__` |
| with the small config and dumping its `state_dict()` with the bundle's legacy |
| naming convention. **Do not use for actual generation** — outputs are noise. |
|
|
