SCAIL-2 14B MLX for mere.run

This repository contains an immutable MLX-native packaging of the official zai-org/SCAIL-2 model for native Swift/MLX inference in mere.run.

It supports reference-subject animation, performer replacement, and up to six palette-masked subjects. The package contains model artifacts only. It does not contain Python, a checkpoint conversion utility, the upstream SCAIL inference repository, Maestro, WanGP, ComfyUI, or translated source code.

Provenance

Source model: zai-org/SCAIL-2
Source model revision: 150cc0ca4e98e50e60b9295dacde39442fdccab2
Packaging: lossless tensor layout/name conversion to safetensors for the independently maintained native Swift/MLX runtime
Precision: BF16 transformer and UMT5, FP16 OpenCLIP and Wan VAE, with explicitly recorded FP32 islands
License: the official SCAIL-2 model card declares the model MIT

MERERUN_CONVERSION.json records the immutable source hashes, output artifact hashes, byte counts, component mapping, and packaging contract. provenance.json retains the exact source component paths and source hashes.

The separately published SCAIL reference-code repository is Apache-2.0. No files from that repository are included in this model package.

Install and use

mere.run model pull video-scail2-14b-mlx

mere.run video animate "a dancer in a red silk dress" \
  --reference reference.png \
  --reference-mask reference-mask.png \
  --driving-video driving.mp4 \
  --driving-mask driving-mask.mov \
  --tail-policy pad-trim \
  --audio-source driving \
  --output result.mp4

Use mere.run video prepare-masks with the separately licensed native vision-segment-sam31 model to prepare palette-safe reference and driving masks. SAM weights are not included here.

Required layout

config.json
model.safetensors.index.json and eight transformer shards
model-fp32-islands.safetensors
t5_encoder.safetensors.index.json and three UMT5 shards
clip.safetensors
vae.safetensors
tokenizer.json
mererun_model.json
provenance.json
MERERUN_CONVERSION.json
LICENSE

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Safetensors

Model size

17B params

Tensor type

BF16

F32

MLX

Hardware compatibility

Quantized

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