Files
diffusers/docs/source/en/using-diffusers/helios.md
dg845 33f785b444 Add Helios-14B Video Generation Pipelines (#13208)
* [1/N] add helios

* fix test

* make fix-copies

* change script path

* fix cus script

* update docs

* fix documented check

* update links for docs and examples

* change default config

* small refactor

* add test

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove register_buffer for _scale_cache

* fix non-cuda devices error

* remove "handle the case when timestep is 2D"

* refactor HeliosMultiTermMemoryPatch and process_input_hidden_states

* Update src/diffusers/pipelines/helios/pipeline_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/pipelines/helios/pipeline_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* fix calculate_shift

* Update src/diffusers/pipelines/helios/pipeline_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* rewritten `einops` in pure `torch`

* fix: pass patch_size to apply_schedule_shift instead of hardcoding

* remove the logics of 'vae_decode_type'

* move some validation into check_inputs()

* rename helios scheduler & merge all into one step()

* add some details to doc

* move dmd  step() logics from pipeline to scheduler

* change to Python 3.9+ style type

* fix NoneType error

* refactor DMD scheduler's set_timestep

* change rope related vars name

* fix stage2 sample

* fix dmd sample

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* remove redundant & refactor norm_out

* Update src/diffusers/pipelines/helios/pipeline_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* change "is_keep_x0" to "keep_first_frame"

* use a more intuitive name

* refactor dynamic_time_shifting

* remove use_dynamic_shifting args

* remove usage of UniPCMultistepScheduler

* separate stage2 sample to HeliosPyramidPipeline

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/models/transformers/transformer_helios.py

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* fix transformer

* use a more intuitive name

* update example script

* fix requirements

* remove redudant attention mask

* fix

* optimize pipelines

* make style .

* update TYPE_CHECKING

* change to use torch.split

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* derive memory patch sizes from patch_size multiples

* remove some hardcoding

* move some checks into check_inputs

* refactor sample_block_noise

* optimize encoding chunks logits for v2v

* use num_history_latent_frames = sum(history_sizes)

* Update src/diffusers/pipelines/helios/pipeline_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* remove redudant optimized_scale

* Update src/diffusers/pipelines/helios/pipeline_helios_pyramid.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* use more descriptive name

* optimize history_latents

* remove not used "num_inference_steps"

* removed redudant "pyramid_num_stages"

* add "is_cfg_zero_star" and "is_distilled" to HeliosPyramidPipeline

* remove redudant

* change example scripts name

* change example scripts name

* correct docs

* update example

* update docs

* Update tests/models/transformers/test_models_transformer_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update tests/models/transformers/test_models_transformer_helios.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* separate HeliosDMDScheduler

* fix numerical stability issue:

* Update src/diffusers/schedulers/scheduling_helios_dmd.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/schedulers/scheduling_helios_dmd.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/schedulers/scheduling_helios_dmd.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/schedulers/scheduling_helios_dmd.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* Update src/diffusers/schedulers/scheduling_helios_dmd.py

Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>

* remove redudant

* small refactor

* remove use_interpolate_prompt logits

* simplified model test

* fallbackt to BaseModelTesterConfig

* remove _maybe_expand_t2v_lora_for_i2v

* fix HeliosLoraLoaderMixin

* update docs

* use randn_tensor for test

* fix doc typo

* optimize code

* mark torch.compile xfail

* change paper name

* Make get_dummy_inputs deterministic using self.generator

* Set less strict threshold for test_save_load_float16 test for Helios pipeline

* make style and make quality

* Preparation for merging

* add torch.Generator

* Fix HeliosPipelineOutput doc path

* Fix Helios related (optimize docs & remove redudant) (#13210)

* fix docs

* remove redudant

* remove redudant

* fix group offload

* Removed fixes for group offload

---------

Co-authored-by: yuanshenghai <yuanshenghai@bytedance.com>
Co-authored-by: Shenghai Yuan <140951558+SHYuanBest@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: SHYuanBest <shyuan-cs@hotmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2026-03-04 21:31:43 +05:30

8.3 KiB

Helios

Helios is the first 14B video generation model that runs at 19.5 FPS on a single NVIDIA H100 GPU and supports minute-scale generation while matching the quality of a strong baseline, natively integrating T2V, I2V, and V2V tasks within a unified architecture. The main features of Helios are:

  • Without commonly used anti-drifting strategies (eg, self-forcing, error-banks, keyframe sampling, or inverted sampling), Helios generates minute-scale videos with high quality and strong coherence.
  • Without standard acceleration techniques (eg, KV-cache, causal masking, sparse/linear attention, TinyVAE, progressive noise schedules, hidden-state caching, or quantization), Helios achieves 19.5 FPS in end-to-end inference for a 14B video generation model on a single H100 GPU.
  • Introducing optimizations that improve both training and inference throughput while reducing memory consumption. These changes enable training a 14B video generation model without parallelism or sharding infrastructure, with batch sizes comparable to image models.

This guide will walk you through using Helios for use cases.

Load Model Checkpoints

Model weights may be stored in separate subfolders on the Hub or locally, in which case, you should use the [~DiffusionPipeline.from_pretrained] method.

import torch
from diffusers import HeliosPipeline, HeliosPyramidPipeline
from huggingface_hub import snapshot_download

# For Best Quality
snapshot_download(repo_id="BestWishYsh/Helios-Base", local_dir="BestWishYsh/Helios-Base")
pipe = HeliosPipeline.from_pretrained("BestWishYsh/Helios-Base", torch_dtype=torch.bfloat16)
pipe.to("cuda")

# Intermediate Weight
snapshot_download(repo_id="BestWishYsh/Helios-Mid", local_dir="BestWishYsh/Helios-Mid")
pipe = HeliosPyramidPipeline.from_pretrained("BestWishYsh/Helios-Mid", torch_dtype=torch.bfloat16)
pipe.to("cuda")

# For Best Efficiency
snapshot_download(repo_id="BestWishYsh/Helios-Distilled", local_dir="BestWishYsh/Helios-Distilled")
pipe = HeliosPyramidPipeline.from_pretrained("BestWishYsh/Helios-Distilled", torch_dtype=torch.bfloat16)
pipe.to("cuda")

Text-to-Video Showcases

Prompt Generated Video
A Viking warrior driving a modern city bus filled with passengers. The Viking has long blonde hair tied back, a beard, and is adorned with a fur-lined helmet and armor. He wears a traditional tunic and trousers, but also sports a seatbelt as he focuses on navigating the busy streets. The interior of the bus is typical, with rows of seats occupied by diverse passengers going about their daily routines. The exterior shots show the bustling urban environment, including tall buildings and traffic. Medium shot focusing on the Viking at the wheel, with occasional close-ups of his determined expression.
A documentary-style nature photography shot from a camera truck moving to the left, capturing a crab quickly scurrying into its burrow. The crab has a hard, greenish-brown shell and long claws, moving with determined speed across the sandy ground. Its body is slightly arched as it burrows into the sand, leaving a small trail behind. The background shows a shallow beach with scattered rocks and seashells, and the horizon features a gentle curve of the coastline. The photo has a natural and realistic texture, emphasizing the crab's natural movement and the texture of the sand. A close-up shot from a slightly elevated angle.

Image-to-Video Showcases

Image Prompt Generated Video
A sleek red Kia car speeds along a rural road under a cloudy sky, its modern design and dynamic movement emphasized by the blurred motion of the surrounding fields and trees stretching into the distance. The car's glossy exterior reflects the overcast sky, highlighting its aerodynamic shape and sporty stance. The license plate reads "KIA 626," and the vehicle's headlights are on, adding to the sense of motion and energy. The road curves gently, with the car positioned slightly off-center, creating a sense of forward momentum. A dynamic front three-quarter view captures the car's powerful presence against the serene backdrop of rolling hills and scattered trees.
A close-up captures a fluffy orange cat with striking green eyes and white whiskers, gazing intently towards the camera. The cat's fur is soft and well-groomed, with a mix of warm orange and cream tones. Its large, expressive eyes are a vivid green, reflecting curiosity and alertness. The cat's nose is small and pink, and its mouth is slightly open, revealing a hint of its pink tongue. The background is softly blurred, suggesting a cozy indoor setting with neutral tones. The photo has a shallow depth of field, focusing sharply on the cat's face while the background remains out of focus. A close-up shot from a slightly elevated perspective.

Interactive-Video Showcases

Prompt Generated Video
The prompt can be found here
The prompt can be found here

Resources

Learn more about Helios with the following resources.