--- license: apache-2.0 base_model: genmo/mochi-1-preview library_name: mlx pipeline_tag: text-to-video tags: - mlx - text-to-video - mochi - apple-silicon --- # Mochi 1 — MLX (SceneWorks) Apple-Silicon (MLX) repackage of [`genmo/mochi-1-preview`](https://huggingface.co/genmo/mochi-1-preview) for the SceneWorks native MLX runtime (`mlx-gen-mochi`). The AsymmDiT transformer ships as three **self-contained, pre-quantized tiers**; the T5-XXL text encoder and AsymmVAE are **shared** across tiers (hosted once as siblings, not duplicated per tier). ## Layout ``` q4/ transformer/model.safetensors + split_model.json + quantize_config.json (~9 GB) q8/ transformer/model.safetensors + split_model.json + quantize_config.json (~12 GB) bf16/ transformer/model.safetensors + split_model.json (~19 GB) text_encoder/ T5-XXL, bf16 (2-shard) + model.safetensors.index.json (~9.5 GB) vae/ AsymmVAE decoder, bf16 (~0.9 GB) tokenizer/ T5 SentencePiece tokenizer ``` To load a tier, point the loader at the tier dir (e.g. `q4/`); the shared `text_encoder/`, `vae/`, and `tokenizer/` resolve from the parent as siblings of the tier subdirs. ## Tiers | Tier | Transformer precision | Approx. size | |------|-----------------------|--------------| | `q4` | 4-bit affine (group 64), 573 quantized Linears | ~9 GB | | `q8` | 8-bit affine (group 64), 573 quantized Linears | ~12 GB | | `bf16` | dense bf16 | ~19 GB | Each tier's `split_model.json` records the quant selection (`quantized`, `quantization_bits`, `quantization_group_size`); a tier dir *is* the quant selection (no on-the-fly requantization). ## Shared components - **`text_encoder/`** — T5-XXL (`google/t5-v1_1-xxl`, 24-layer encoder, `d_model=4096`) hosted in **bf16** (2-shard set + a matching `model.safetensors.index.json`), bit-identical to round-to-bf16 of the upstream fp32 weights (the precision the reference pipeline loads at). - **`vae/`** — `AutoencoderKLMochi` decoder in bf16. - **`tokenizer/`** — the T5 SentencePiece tokenizer. ## Source & license Repackaged from [`genmo/mochi-1-preview`](https://huggingface.co/genmo/mochi-1-preview). Licensed **Apache-2.0**, matching the upstream Mochi 1 release. Weights are unchanged apart from the per-tier quantization of the transformer and the dtype/shard repackaging described above.