Instructions to use YossiIsr/joyai-video-edit-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YossiIsr/joyai-video-edit-fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YossiIsr/joyai-video-edit-fp8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
JoyAI-Video-Edit, FP8 (RTX 5090 serving layout)
An FP8 conversion by Plotin of JoyAI-Video-Edit
(DiT checkpoint dit/joyai_video_edit_dit_0811.pth), packaged with its VAE and text encoder so one repo
holds everything the streaming server loads. Not affiliated with or endorsed by JD or Xiaomi.
| Path | What | From |
|---|---|---|
dit/joyai_video_edit_dit_0811_fp8.safetensors |
DiT with the img/txt attention and MLP Linears in FP8 e4m3, per-channel scales; other tensors bf16 | converted from JoyAI-Video-Edit dit/joyai_video_edit_dit_0811.pth |
vae/ |
unchanged | JoyAI-Video-Edit vae/ |
text_encoder/ |
unchanged (weights, tokenizer, configs, model card) | MiMo-VL-7B-RL-2508 |
What the conversion is. The upstream server converts these Linears to FP8 itself every time it loads
(Fp8Linear.from_linear, JOYOMNI_FP8_IMG=1 JOYOMNI_FP8_TXT=1). This file stores that result, made with
JOYOMNI_FP8_FAST_ACCUM=1 (the RTX 5090 recipe), so a server start skips reading the 32.5 GB bf16
checkpoint and quantizing it. FP8 weights are stored transposed (row-major); the file metadata records
the format (joyai-fp8-presaved-v1) and the fast-accum setting. Loading it needs a small patch to the
upstream server (build the model on the meta device, fill tensors from this file); the stock server
cannot load it.
Licenses
- JoyAI-Video-Edit (DiT, VAE): Apache License 2.0, see
LICENSEandNOTICE. - MiMo-VL-7B-RL-2508 (
text_encoder/): MIT, as declared on its model card; seetext_encoder/LICENSE.
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