Instructions to use Massyzs/videoeditor-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Wan2.2
How to use Massyzs/videoeditor-14b with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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videoeditor-14b
Code: https://github.com/massyzs/Video-Editor-MoE (scripts/moe/videoeditor-14b/)
Optimizer state: removed (weights only).
Package contents
The weights are shipped as a tar.gz stream split into ~20 GB chunks (Hugging Face limits single files to 50 GB).
| chunk | size | sha256 |
|---|---|---|
videoeditor-14b.tar.gz.part-00 |
21.47 GB | 7e51c27d3102d5da475dd9f906d5e6902fada5a43960ba3decfd4bfb7db4ab6c |
videoeditor-14b.tar.gz.part-01 |
0.95 GB | 11e34da0e0c4657b68313a5e8fd8c1dcb8695f40c6569d3184b515d3eb82bceb |
Total: 2 chunks, 22.42 GB compressed / 27.97 GB extracted.
Reassemble and verify:
huggingface-cli download Massyzs/videoeditor-14b --local-dir videoeditor-14b-package # after your access request is approved
cd videoeditor-14b-package
cat videoeditor-14b.tar.gz.part-* | tar -xzf - -C <BASE_DIR>/ckpt/ # creates <BASE_DIR>/ckpt/videoeditor-14b/
cp SHA256SUMS.contents <BASE_DIR>/ckpt/ && (cd <BASE_DIR>/ckpt && sha256sum -c SHA256SUMS.contents) # optional check
MANIFEST.json lists every payload file with its size and sha256, and every chunk with its sha256 (SHA256SUMS.parts).
Extracted files:
| file | size | sha256 |
|---|---|---|
videoeditor-14b/meta.json |
455 B | 76c0486df3e6824f58ff3033a669d6fec1efcf148e9b94b6bfb369b2f80d9c04 |
videoeditor-14b/moe_v3_1_trainable.safetensors |
27.97 GB | b7dea5b5ccf708eea36376243099f175bc03272748fe854b4c49b79e14ae8e5a |
Base weights you also need
The package contains the full DiT weights (28.0 GB bf16); only the MLLM encoder (qwen/), the VAE and moe_expert_init.safetensors are needed in addition.
All frozen base components are published, already converted to the layout this code expects, in
Massyzs/kiwi-edit-5b-instruct-only-videoxfun:
huggingface-cli download Massyzs/kiwi-edit-5b-instruct-only-videoxfun --local-dir <BASE_DIR>/ckpt/kiwi-edit-instruct-only-videoxfun
See BASE_WEIGHTS.md for where each component comes from (Kiwi-Edit, Wan2.2) and its checksum.
Inference
python scripts/moe/videoeditor-14b/moe_v3_1_infer.py --base_dir <BASE_DIR> --ckpt <BASE_DIR>/ckpt/videoeditor-14b \
--src_video input.mp4 --prompt "Replace the red car with a blue truck" --name edited --out_dir <OUT_DIR>
# multi-step instruction: --prompts "Remove the dog ||| Convert to oil painting style"
Single 80 GB GPU. Output: <OUT_DIR>/<name>.mp4 plus lossless PNG frames in <OUT_DIR>/frames/<name>/.
Training
The training launcher is scripts/moe/videoeditor-14b/train_multinode.sh in the code repository: edit the configuration block at the top
(BASE_DIR, data paths, node addresses) and run bash scripts/moe/videoeditor-14b/train_multinode.sh <node rank> on every node.
scripts/moe/videoeditor-14b/train_smoke.sh is a single-node smoke test. The data formats are described in docs/DATA.md of the repository.
License
The released weights and code are under Apache-2.0. The frozen base components (Kiwi-Edit MLLM encoder / DiT base, Wan2.2 VAE) are not redistributed here and remain subject to their own licenses.
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linyq/kiwi-edit-5b-instruct-only-diffusers