Release minimax_h3_hyperflow_8step_v1.0.safetensors

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LICENSE

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+MiniMax H3 COMMUNITY LICENSE AGREEMENT
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NOTICE

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+MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax. All Rights Reserved.
+
+The HyperFlow LoRA weights in this repository (minimax_h3_hyperflow_*.safetensors) are a Model Derivative of
+MiniMax-H3 (https://huggingface.co/MiniMaxAI/MiniMax-H3) as defined in Section I.11 of that Agreement. They were
+created by the HyperFlow authors (Copyright 2026 The HyperFlow authors) and are distributed under the same
+MiniMax H3 Community License Agreement, a copy of which is included in this repository as LICENSE.
+
+Modifications (Section III.2): each LoRA file is a new file trained against MiniMaxAI/MiniMax-H3 at the revision
+recorded in its header (`base_model_revision`). No file of MiniMax-H3 is modified or redistributed here; the base
+weights, VAEs and text encoder remain the official ones.
+
+HyperFlow is not an official MiniMax product and is not affiliated with or endorsed by MiniMax.
+Powered by MiniMax H3.

README.md

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+---
+license: other
+license_name: minimax-h3-community-license-agreement
+license_link: LICENSE
+base_model: MiniMaxAI/MiniMax-H3
+base_model_relation: adapter
+pipeline_tag: image-text-to-video
+library_name: hyperflow-h3
+tags:
+  - lora
+  - minimax-h3
+  - diffusers
+  - video-generation
+  - audio-video-generation
+  - text-to-video
+  - image-to-video
+  - image-text-to-video
+  - text-to-audio-video
+  - image-to-audio-video
+  - reference-to-audio-video
+  - flow-matching
+  - distillation
+  - self-distillation
+  - few-step
+---
+
+# HyperFlow for MiniMax-H3
+
+> By downloading or using these weights you accept the [MiniMax H3 Community License Agreement](LICENSE), including
+> its territorial scope (not licensed in the EU, UK, South Korea or the US without MiniMax's separate authorization)
+> and its Acceptable Use Policy. See [License](#license). Not an official MiniMax product.
+
+HyperFlow is [Video Rebirth](https://www.videorebirth.com/)'s 8-step LoRA for
+[MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3), obtained by data-free flow self-distillation and running
+on the official [diffusers Modular Pipeline](https://huggingface.co/docs/diffusers/main/api/pipelines/minimax_h3).
+Diffusers' default 50-point sigma schedule performs 49 model forwards; HyperFlow performs 8. The base weights, VAEs,
+conditioner and workflows (`t2va`, `fl2va`, `ref2va`, all video + audio) stay the official ones. This repository
+holds the LoRA only; the loader and examples live at
+[github.com/Video-Rebirth/hyperflow](https://github.com/Video-Rebirth/hyperflow).
+
+| | |
+|---|---|
+| Base model | [`MiniMaxAI/MiniMax-H3`](https://huggingface.co/MiniMaxAI/MiniMax-H3) (revision recorded in the file header) |
+| Adapter | PEFT LoRA, rank 256 / alpha 256, on attention, feed-forward and both time embedders (316 modules); 2.8 GB |
+| Sampling | 8 forward passes on a fixed sigma grid stored in the file (video shift 12, audio shift 3) |
+| Workflows | `t2va`, `fl2va` and `ref2va`, one file for all three (`ref2va` loads it onto `transformer_ref/`) |
+| Speed-up | ~3x end to end against the 49-NFE Diffusers baseline (~60 s vs ~175 s per clip on 4x H200) |
+| Optional | Ulysses context parallel on up to 4 GPUs; FlashAttention-3; NVIDIA Sol-Attn sparse attention |
+| License | [MiniMax H3 Community License Agreement](LICENSE); code on GitHub is Apache-2.0. See [License](#license) |
+
+**Not a generic LoRA.** The file carries keys for a second time embedder that only exists once the HyperFlow loader
+has installed it, and the step count comes from the file. Load it with `load_hyperflow_lora` from the
+`hyperflow-h3` package, not with diffusers' `load_lora_weights` / `load_lora_adapter`.
+
+## Files
+
+| File | `hyperflow_version` | Notes |
+|---|---|---|
+| `minimax_h3_hyperflow_8step_v1.0.safetensors` | `1.0` | **default**: what a bare repo id loads. First release |
+| `hyperflow.json` | | Manifest: the `default` file and every file's `hyperflow_version` and `sha256` |
+| `LICENSE`, `NOTICE` | | MiniMax H3 Community License Agreement and the notice it requires |
+
+A published file name is never reused: pin one with `filename=` (or `--weights-filename`) and it stays what it is.
+A bare repo id follows the manifest's `default`, so it picks up new versions as they ship; `revision=` pins a tag or
+commit of this repository.
+
+## Usage
+
+```bash
+pip install "hyperflow-h3[examples] @ git+https://github.com/Video-Rebirth/hyperflow.git"
+```
+
+Python ≥ 3.10, diffusers ≥ 0.40.0 (the first release with the MiniMax-H3 Modular Pipeline and its context parallel
+plan), transformers ≥ 4.57 (Qwen3-VL). The `examples` extra adds PyAV for writing the output video.
+
+```python
+import torch
+from diffusers import ComponentsManager
+from diffusers.utils import load_image
+from hyperflow_h3 import hyperflow_blocks, load_hyperflow_lora
+
+manager = ComponentsManager()
+blocks = hyperflow_blocks("fl2va")                              # official workflow, two blocks swapped
+pipe = blocks.init_pipeline("MiniMaxAI/MiniMax-H3", components_manager=manager)
+pipe.load_components(dtype=torch.bfloat16)
+load_hyperflow_lora(pipe, "videorebirth/hyperflow")  # LoRA + two-time embedder + 8-step grid
+
+# The official single-GPU recipe (auto CPU offload), armed only now: registering a component resets the margin.
+# 24 GB is the margin validated on H200; the official recipe's 12 GB starves the denoiser there. See Performance.
+manager.enable_auto_cpu_offload(device="cuda", memory_reserve_margin="24GB")
+
+out = pipe(
+    prompt="A red fox trotting through a snowy pine forest",
+    image=load_image("first.png"),
+    num_frames=124,
+    generator=torch.Generator().manual_seed(42),
+    output=["videos", "audio", "sampling_rate"],
+)
+```
+
+- Do not pass `num_inference_steps`: the step count and sigma grid come from the weights file; another count raises.
+- Every other input (`prompt`, `image`, `last_image`, `references`, `height`, `width`, `num_frames`, `generator`)
+  is the official pipeline's.
+- Other workflows: `hyperflow_blocks("t2va")` (no `image`) and `hyperflow_blocks("ref2va")` (`references=`; the
+  same weights file is loaded onto `transformer_ref`).
+- Prompting: MiniMax's hosted H3-Context-IR prompt refinement is not part of the open weights, so prompts follow the
+  base model's [prompting guidance](https://huggingface.co/MiniMaxAI/MiniMax-H3#prompting-guidance) as they do in
+  the base Diffusers pipeline.
+
+**Pinning and offline use.** `load_hyperflow_lora` takes this repo id, a local directory or a `.safetensors` file.
+Manifest and weights are fetched once into the `huggingface_hub` cache and keep working under `HF_HUB_OFFLINE=1`.
+
+```python
+load_hyperflow_lora(pipe, "videorebirth/hyperflow", filename="minimax_h3_hyperflow_8step_v1.0.safetensors")
+load_hyperflow_lora(pipe, "/weights/hyperflow")  # from `hf download videorebirth/hyperflow --local-dir /weights/hyperflow`
+```
+
+**Example commands, several GPUs, Sol-Attn.** The package installs `hyperflow-h3-fl2va` and
+`hyperflow-h3-ref2va`; the GitHub repository also has [`examples/`](https://github.com/Video-Rebirth/hyperflow/tree/main/examples)
+source-tree launchers. They provide Ulysses sequence parallel over up to 4 GPUs (the degree MiniMax serves the model
+with), FlashAttention-3, NVIDIA Sol-Attn and `--baseline` (Diffusers' default 50 sigma points / 49 NFE on the same
+seed, for an A/B). Fully offline runs take a local weights file and a local MiniMax-H3 snapshot.
+
+```bash
+hyperflow-h3-fl2va --prompt "..." --image first.png            # first frame -> video+audio, up to 4 GPUs
+hyperflow-h3-ref2va --prompt "..." --ref subject.png --ref clip.mp4 --ref voice.wav
+hyperflow-h3-fl2va --prompt "..." --image first.png --gpus 1   # the official single-GPU recipe
+```
+
+## Performance
+
+HyperFlow (8 NFE, 9 sigma points) against the base pipeline at Diffusers' default (49 NFE, 50 sigma points) on the
+same clip: `fl2va`, 124 frames, 1344x768, seed 0, dense SDPA attention. Pipeline time covers text encoding, denoising
+and decoding; process start-up and weight loading add ~30 s.
+
+| | Base, 49 NFE | HyperFlow, 8 NFE | Speed-up |
+|---|---|---|---|
+| 4x H200, Ulysses degree 4 | ~175 s | ~60 s | 2.9x |
+| 1x H200, auto CPU offload | ~395 s | ~130 s | 3.0x |
+
+The speed-up is below the 49:8 NFE ratio because text encoding and VAE decoding, which HyperFlow leaves unchanged,
+now take much of the run. Peak accelerator memory is ~80 GB per card either way (the LoRA adds 2.8 GB). The
+single-GPU row uses `memory_reserve_margin="24GB"`, not the official recipe's 12 GB: on a 141 GB H200 a smaller margin
+evicts the 10 GB VAE instead of the 62 GB text encoder when the DiT arrives and starves the denoiser. An 80 GB card
+is untested.
+
+With a fixed seed a run reproduces itself (audio bit-identical, video PSNR ≈ 43–50 dB, a residue of the VAE decode).
+Across GPU counts or attention backends the clip is only visibly similar (PSNR ≈ 27 dB and ≈ 34 dB): sharding and
+kernels change the bf16 reduction order. NVIDIA Sol-Attn sparse attention, optional and off by default, is a further
+approximation (PSNR ≈ 23 dB against the dense run); check its output before adopting it.
+
+## Quality
+
+HyperFlow is a self-distillation: the base model is the only teacher. Against the base pipeline at 49 NFE, on the
+same seeds, four things stand out:
+
+- **More balanced capabilities**
+- **Better camera control**
+- **Better consistency**
+- **Better materials and detail**
+
+<!-- TODO(comparison): side-by-side clips, base 49 NFE vs HyperFlow 8 NFE, same seed, 124 frames at 1344x768.
+| Prompt | Base, 49 NFE | HyperFlow, 8 NFE |
+|---|---|---|
+| ... | ... | ... |
+-->
+
+Judge on your own prompts: `--baseline` in the example scripts renders both pipelines on one seed.
+
+## How it works
+
+Three additions to the official pipeline, all reversible (`disable_hyperflow`):
+
+- **Two-time conditioning.** The LoRA was trained with both the current time `t` and the step's endpoint `r` (a
+  flow-map formulation). A `TwoTimeEmbedder` wraps the base `time_embedder`, adds a LoRA'd copy for `r`, and blends
+  the two embeddings with a fixed gate stored in the file. Conditioning rows (`fl2va` keyframes, `ref2va`
+  references) keep `r = t`, so they stay pinned exactly as in the official denoiser.
+- **8-step schedule.** The official timestep block is replaced by the trained sigma grid (video and audio shifts
+  included); the denoising loop hands each step's endpoints to the embedder. Nothing else in the workflow changes.
+- **One file, three workflows.** `t2va` and `fl2va` share `transformer/`. `ref2va` runs the same file on
+  `transformer_ref/`, which works because the adapter never touches `adaln_proj`, the carrier of the reference
+  conditioning.
+
+**File format.** A plain `safetensors` file: PEFT-style keys (`transformer.<module>.lora_A.weight`; bf16 for the
+DiT blocks, fp32 for the two time embedders) plus a self-describing header (`hyperflow_sigmas`, `hyperflow_gate`,
+`lora_rank`, `lora_alpha`, `base_model`, `base_model_revision`, …):
+
+```python
+from hyperflow_h3 import read_metadata
+
+meta = read_metadata("minimax_h3_hyperflow_8step_v1.0.safetensors")  # header only, no tensors loaded
+meta.base_model_revision, meta.sigmas, meta.gate
+```
+
+## Intended use and limitations
+
+- A drop-in speed-up for MiniMax-H3 inference on diffusers: same inputs, same outputs (video + stereo audio), ~3x
+  faster end to end. It is a distilled few-step sampler, so compare against the base Diffusers pipeline on your own
+  prompts before adopting it (`--baseline` in the example scripts runs both on the same seed).
+- Prompt following, languages, biases and failure modes are the base model's, which the distillation is designed to
+  keep ([Quality](#quality)); see the [MiniMax-H3 model card](https://huggingface.co/MiniMaxAI/MiniMax-H3).
+- Training code is not part of this release.
+- Use is bound by the license below, including its territorial scope and its Acceptable Use Policy.
+
+## License
+
+The LoRA weights are a Model Derivative of MiniMax-H3 and are distributed under the
+[MiniMax H3 Community License Agreement](LICENSE), the base model's license, with no additional terms. By
+downloading or using them you accept that Agreement. In particular:
+
+- **Territory.** The license is granted worldwide **excluding the European Union, the United Kingdom, the Republic of
+  Korea and the United States of America**. Individuals and organizations there must obtain MiniMax's authorization
+  before downloading ([application form](https://platform.minimax.io/h3-license), open to individuals as well;
+  [Q&A](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/QA-about-License.md)).
+- **Redistribution.** Pass on a copy of the Agreement and the [`NOTICE`](NOTICE) file, mark modified files, and do not
+  impose additional or different terms (Section III).
+- **Disclosure.** Content generated with these weights and posted publicly must be clearly disclosed as AI-generated
+  (Acceptable Use Policy, item 12). Naming "MiniMax H3" is encouraged, not required.
+- **Commercial use.** Products or services with more than 20 million US dollars yearly revenue need MiniMax's prior
+  written authorization (api@minimax.io). Products and services built with the weights must display "MiniMax H3" on
+  their user interface (Section IV.2); this applies to what you build, not to finished videos published on
+  third-party platforms.
+- **Hosted services.** If you serve generations to third parties, you must implement the safeguards in Section V.5
+  and bind your users to the same use restrictions (Section V.2).
+- **Use restrictions.** Section V and the Acceptable Use Policy (Exhibit A) apply to the weights and to their outputs;
+  outputs may not be used to improve other AI models.
+- **Upstream text.** [`LICENSE`](LICENSE) is the August 2, 2026 text. MiniMax may update the Acceptable Use Policy;
+  the version in the [upstream repository](https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE) governs.
+
+The loader and example scripts on [GitHub](https://github.com/Video-Rebirth/hyperflow) are separate software under
+the Apache License 2.0.
+
+HyperFlow is developed by Video Rebirth. It is not an official MiniMax product and is not affiliated with or
+endorsed by MiniMax. Powered by MiniMax H3.
+
+## Acknowledgements
+
+- **[MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3)** ([GitHub](https://github.com/MiniMax-AI/MiniMax-H3)): the base model, VAEs, conditioner and official workflows.
+- **AnyFlow** ([GitHub](https://github.com/NVlabs/AnyFlow); Gu et al., 2026): the flow-map formulation behind the two-time `(t, r)` conditioning.
+- **[diffusers](https://github.com/huggingface/diffusers)**: the Modular Pipeline and context parallel plan the loader builds on.
+- **FlashAttention-3** and **Sol-Attn** ([GitHub](https://github.com/NVlabs/Sana/tree/main/techniques/sparse_backends); Li et al., 2026): optional attention kernels.
+
+Thanks to their authors.

hyperflow.json

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+  "default": "minimax_h3_hyperflow_8step_v1.0.safetensors",
+  "weights": {
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+      "hyperflow_version": "1.0",
+      "sha256": "9297f4505bfdef59c3014d11274411809c19b0abfe26161cab2b425a696df447"
+    }
+  }
+}

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