Text-to-Video
Diffusers
Safetensors
MiniMax H3
English
freevideo
vdn
fp8
image-to-video
video-generation
audio-generation
Instructions to use OpenVDN/vdn-minimax-h3-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OpenVDN/vdn-minimax-h3-edge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenVDN/vdn-minimax-h3-edge", 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
Add rowwise FP8 variant; preserve tensorwise model and selective downloads
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- MODIFICATIONS.md +4 -0
- README.md +25 -41
- SHA256SUMS +261 -3
- bundle.json +0 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/00.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/00.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/01.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/01.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/02.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/02.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/03.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/03.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/04.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/04.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/05.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/05.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/06.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/06.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/07.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/07.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/08.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/08.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/09.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/09.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/10.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/10.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/11.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/11.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/12.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/12.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/13.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/13.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/14.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/14.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/15.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/15.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/16.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/16.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/17.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/17.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/18.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/18.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/19.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/19.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/20.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/20.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/21.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/21.safetensors +3 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/22.json +4 -0
- rowwise/cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/22.safetensors +3 -0
MODIFICATIONS.md
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The optional original projection source is pinned to the prior complete repository revision. It is not part of the default download. A modulation-changing adapter or unsupported schedule may request it explicitly through the engine's compatibility path.
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The new catalog, identity records, manifest and model card describe this format change. LICENSE is an unmodified copy of the upstream agreement; NOTICE preserves the upstream attribution.
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The optional original projection source is pinned to the prior complete repository revision. It is not part of the default download. A modulation-changing adapter or unsupported schedule may request it explicitly through the engine's compatibility path.
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The new catalog, identity records, manifest and model card describe this format change. LICENSE is an unmodified copy of the upstream agreement; NOTICE preserves the upstream attribution.
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## Rowwise variant
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`rowwise/cache/` adds the existing official per-channel FP8 weight format. The 51 block/root archives carry modification notices in their safetensors metadata. Their tensor payloads are copied unchanged from the previously prepared rowwise cache; no requantization or training occurs during packaging. The portable modulation constants match the same original projection and time-embedding weights. Existing `cache/` per-tensor files and original licenses are unchanged.
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# VDN-H3 Edge
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Prepared FP8 weights and
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## Compatibility and validation
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- Format: `freevideo-fp8-slim-v1` with `freevideo-adaln-v2` constants. This is an engine package, not a generic single-file Diffusers or ComfyUI checkpoint.
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- FP8 scales: **per-tensor**. Automatic setup uses this format for Blackwell. A native rowwise path needs a different FP8 artifact; portable AdaLN does not convert one FP8 scale format into another.
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- Requires the current FreeVideo engine with `freevideo-fp8-slim-v1` support, available from [FlashML-org/FreeVideo](https://github.com/FlashML-org/FreeVideo). The model is public and needs no Hugging Face login. Older engines without slim-format support cannot read this release.
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- One complete 1344×768, 362-frame, eight-step T2VA request on Linux SM120 was compared with the original full prepared model, using the same seed, conditioning, FP8 policy and Sage2 configuration. Video latents, audio latents, raw RGB and raw float audio were all **bitwise equal**. The runtime loaded all 50 modulation tables and read no omitted projection groups.
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- This validates packaging and reuse for that request. It does not certify other GPUs or every adapter/task combination, and makes no new minimum-memory or speed claim.
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## Download and use
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```bash
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hf download OpenVDN/vdn-minimax-h3-edge --local-dir models/vdn-h3-edge
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```
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```bash
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./setup.sh --cache ./models/vdn-h3-edge/cache
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```
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## License
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# VDN-H3 Edge
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Prepared FP8 weights and portable AdaLN constants for [FreeVideo](https://github.com/FlashML-org/FreeVideo). Powered by MiniMax H3.
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Two FP8 formats live in this repository. **FreeVideo downloads only the matching format**, about **22.9 GB / 21.4 GiB**, plus the separately installed text encoder and decoders. It does not download both variants or the original transformer weights.
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## Formats
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| Directory | Quantization | FreeVideo automatic route |
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| --- | --- | --- |
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| `cache/` | Per-tensor FP8 | Blackwell, including RTX 50 |
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| `rowwise/cache/` | Per-channel FP8 weights | Ada / RTX 40 and Hopper / SM90; Ampere / RTX 30 uses this storage with BF16 compute |
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These routes preserve the engine's existing arithmetic. Ada also supports per-tensor FP8; keeping its current rowwise policy is a software/output compatibility choice. Windows rowwise uses FreeVideo's scalar FP8 GEMM plus fused row/column scaling, because the pinned PyTorch Windows build excludes its native rowwise implementation. Linux uses the native rowwise path. SM90's favorable rowwise dispatch does not establish equal performance on every architecture or shape.
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The per-tensor model files are unchanged. Each format has its own immutable installer pin, so adding rowwise does not move or redownload an existing per-tensor installation. The repositories on [Hugging Face](https://huggingface.co/OpenVDN/vdn-minimax-h3-edge) and [ModelScope](https://modelscope.ai/models/OpenVDN/vdn-minimax-h3-edge) contain the same payload. Setup selects a working source and resumes interrupted files.
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## Use
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Install [FreeVideo](https://github.com/FlashML-org/FreeVideo) and let setup select the files automatically. The model is public; no login is needed to download it.
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For a manual download, choose **one** command:
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```bash
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# Blackwell / RTX 50
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hf download OpenVDN/vdn-minimax-h3-edge --include "cache/**" "config/**" "LICENSE" "NOTICE" "OPENVDN-CODE-LICENSE" "MODIFICATIONS.md" --local-dir models/vdn-h3-edge
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# RTX 30 / RTX 40 / Hopper
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hf download OpenVDN/vdn-minimax-h3-edge --include "rowwise/**" "config/**" "LICENSE" "NOTICE" "OPENVDN-CODE-LICENSE" "MODIFICATIONS.md" --local-dir models/vdn-h3-edge
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```
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Then select the downloaded directory in the FreeVideo launcher. Linux source users can pass `./setup.sh --cache ./models/vdn-h3-edge/cache` or `./setup.sh --cache ./models/vdn-h3-edge/rowwise/cache`. Windows source users use the same `--cache` option with `setup.cmd`. Avoid an unfiltered repository download if you only need one format.
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## Portable AdaLN constants
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Both formats contain the same two table sets: standard eight-step text-to-video and visual-keyframe schedules. I2VA, L2VA, FL2VA and visual-reference requests share the visual schedule where the engine's exact timestep contract matches. Prompt, seed, dimensions, duration, GPU model and Torch/CUDA versions do not require regenerating these stored constants.
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Original AdaLN projections are omitted, saving approximately 26.02 GB per installation. Unsupported schedules or modulation-changing LoRAs can use the optional original projections from the pinned [historical revision](https://huggingface.co/OpenVDN/vdn-minimax-h3-edge/tree/4f16eb1066d96592b84be0de532069f5d69fcfa9). Ordinary attention/FF LoRAs retain the tables.
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## Validation and provenance
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The formats derive from the same 101 merged BF16 groups. Rowwise packaging copies all 363 previously prepared FP8 matrices without requantization; modification notices change headers only. Original projection identities and time-embedding tensors match the portable assets. All 50 text-only tables are byte-identical to the earlier rowwise generation cache.
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The earlier rowwise native/Windows-compatibility comparison completed an eight-step 1344×768, 243-frame request on Linux SM120 with bit-identical video/audio latents, decoded RGB and audio. The existing per-tensor slim package was checked against the full prepared model on a complete 1344×768, 362-frame request, also bit-identically. This publication adds a byte-preserving rowwise package; it adds no new physical Hopper, Ada or Windows benchmark.
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Individual cache format: `freevideo-fp8-slim-v1`; portable tables: `freevideo-adaln-v2`. These are FreeVideo engine packages. The source is `OpenVDN/vdn-minimax-h3@751739ee5b9e3ac802dca5d5111075fdaeb47885`; no additional training was performed. `bundle.json`, `rowwise/cache/publication.json`, `SHA256SUMS` and `READY.json` record source identities and publication verification. [MODIFICATIONS.md](MODIFICATIONS.md) describes the changes; [NOTICE](NOTICE) retains attribution.
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## License
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SHA256SUMS
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59b99642b95ea21630e311198ddbfffbfe05aadba0c2f5d884cbdf4efcc90f44 LICENSE
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-
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6b6671af343af83d5c8bff1b13875e9fe8ffd338f43d4343fa9efa96f49cf81f NOTICE
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cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 OPENVDN-CODE-LICENSE
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9f4e7a1a78227586e374f8400e5e43691d7acddea4a7025b8285faa29e72a166 cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/00.json
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5f8393a55e4508b4f03a2325848cf74fa854dfdf84a0d949e9614079acd2bf80 cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/00.safetensors
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df9828c32a00ad365559189433b3f9fb00fa5eb5ba8305479c8ad19f4e16e12e cache/adaln-tables-v2-222c457ff086c1fbf4b633e1/01.json
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decb06ac7e664610f677fb445318502b3c51f9c1b8603a2cdd00b16042be5bc8 config/stage-dmd-step-250/linear_branch/config.json
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54054ceb1c91b3fdf7fa0278e4a8841c127e8cf666b5e240d69613661f9d3e9e config/stage-dmd-step-250/metadata.json
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4171f4384e952f1f73467981a893440c03298af4956b947e2c8a857ba9f5a62b config/stage-dmd-step-250/model_spec.json
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ADDED
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ADDED
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ADDED
|
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ADDED
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ADDED
|
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|
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ADDED
|
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