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Опубликована
16 мар 2025

LTX-Video-0.9.1

Генерация видеоТекст → видео3 профессии

Производная модели Lightricks/LTX-Video-0.9.5. Диффузионная модель Lightricks для генерации видео по англоязычному текстовому описанию или исходному изображению.

397скачиваний за 30 дней11лайковвеса обновлены6 мая 2025

Бенчмарки

Как модель справилась с задачами пользователей ailist и что о ней публикуют открытые лидерборды

Тесты пользователейпока нет

Никто ещё не опубликовал тест этой модели. Соберите бенчмарк из своих задач — результат появится здесь.

  1. Добавьте модель в бенчмарк

    Вместе с другими моделями категории «Видео» — сравнение идёт внутри одной категории.

  2. Опишите свои задачи

    Напишите запросы, при необходимости приложите файлы и эталонные ответы.

  3. Запустите и опубликуйте

    Модели сгенерируют результат по каждой задаче. Опубликованный тест появится на этой странице.

Публичные оценки

Из открытых лидербордов. Сравнивайте результаты одного теста при одинаковых условиях — отсутствие оценки не значит, что модель хуже.

В подключённых источниках результатов для этой модели пока нет.

Что умеет модель

Описание составлено по карточке модели и метаданным Hugging Face

Карточка модели Lightricks/LTX-Video-0.9.1 на Hugging Face совпадает с карточкой Lightricks/LTX-Video-0.9.5, поэтому описание составлено по ней.

LTX-Video-0.9.5 — диффузионная модель генерации видео, разработанная Lightricks. Она создаёт видео по текстовому запросу, а также поддерживает сценарий image-to-video с текстом и исходным изображением. Модель построена на архитектуре Diffusion Transformer (DiT) и доступна для работы через Diffusers.

Модель предназначена для генерации реалистичных и разнообразных видеосцен. В карточке семейства заявлена генерация видео с частотой 30 кадров в секунду и разрешением до 1216×704 быстрее реального времени; оптимальные рекомендации для разрешения и длины ролика зависят от версии и настроек. Запросы рекомендуется составлять на английском языке. Для разрешения подходят размеры, кратные 32, а число кадров — вида 8n+1; модели семейства лучше работают при разрешении ниже 720×1280 и числе кадров менее 257.

Модель подходит для создания видеоматериалов по описанию сцены и анимации исходного изображения. Она может не точно следовать запросу, результат зависит от формулировки промпта, а модель не предназначена для предоставления фактической информации и может усиливать социальные предубеждения. Метаданные указывают лицензию «other»; README перечисляет отдельные лицензии версий семейства, но не раскрывает условия конкретно версии 0.9.5.

Сценарии применения

  • создание короткого видео по текстовому описанию сцены
  • анимация исходного изображения по текстовому запросу
  • подготовка видеоконцептов для творческих проектов
  • генерация реалистичных сцен для прототипов и демонстраций

Ограничения

Модель может не точно следовать запросу, а качество зависит от стиля и подробности англоязычного промпта. Она не предназначена для выдачи фактической информации и может усиливать предубеждения из обучающих данных.

Для каких профессий подходит3

Разделы каталога профессий, в задачах которых используется эта модель

Все профессии

Карточка модели

README от автора на Hugging Face, как он его опубликовал

Открыть на Hugging Face

LTX-Video Model Card

This model card focuses on the model associated with the LTX-Video model, codebase available here.

LTX-Video is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 30 FPS videos at a 1216×704 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content. We provide a model for both text-to-video as well as image+text-to-video usecases

example1A woman with long brown hair and light skin smiles at another woman...A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage.example2A woman walks away from a white Jeep parked on a city street at night...A woman walks away from a white Jeep parked on a city street at night, then ascends a staircase and knocks on a door. The woman, wearing a dark jacket and jeans, walks away from the Jeep parked on the left side of the street, her back to the camera; she walks at a steady pace, her arms swinging slightly by her sides; the street is dimly lit, with streetlights casting pools of light on the wet pavement; a man in a dark jacket and jeans walks past the Jeep in the opposite direction; the camera follows the woman from behind as she walks up a set of stairs towards a building with a green door; she reaches the top of the stairs and turns left, continuing to walk towards the building; she reaches the door and knocks on it with her right hand; the camera remains stationary, focused on the doorway; the scene is captured in real-life footage.example3A woman with blonde hair styled up, wearing a black dress...A woman with blonde hair styled up, wearing a black dress with sequins and pearl earrings, looks down with a sad expression on her face. The camera remains stationary, focused on the woman's face. The lighting is dim, casting soft shadows on her face. The scene appears to be from a movie or TV show.example4The camera pans over a snow-covered mountain range...The camera pans over a snow-covered mountain range, revealing a vast expanse of snow-capped peaks and valleys.The mountains are covered in a thick layer of snow, with some areas appearing almost white while others have a slightly darker, almost grayish hue. The peaks are jagged and irregular, with some rising sharply into the sky while others are more rounded. The valleys are deep and narrow, with steep slopes that are also covered in snow. The trees in the foreground are mostly bare, with only a few leaves remaining on their branches. The sky is overcast, with thick clouds obscuring the sun. The overall impression is one of peace and tranquility, with the snow-covered mountains standing as a testament to the power and beauty of nature.
example5A woman with light skin, wearing a blue jacket and a black hat...A woman with light skin, wearing a blue jacket and a black hat with a veil, looks down and to her right, then back up as she speaks; she has brown hair styled in an updo, light brown eyebrows, and is wearing a white collared shirt under her jacket; the camera remains stationary on her face as she speaks; the background is out of focus, but shows trees and people in period clothing; the scene is captured in real-life footage.example6A man in a dimly lit room talks on a vintage telephone...A man in a dimly lit room talks on a vintage telephone, hangs up, and looks down with a sad expression. He holds the black rotary phone to his right ear with his right hand, his left hand holding a rocks glass with amber liquid. He wears a brown suit jacket over a white shirt, and a gold ring on his left ring finger. His short hair is neatly combed, and he has light skin with visible wrinkles around his eyes. The camera remains stationary, focused on his face and upper body. The room is dark, lit only by a warm light source off-screen to the left, casting shadows on the wall behind him. The scene appears to be from a movie.example7A prison guard unlocks and opens a cell door...A prison guard unlocks and opens a cell door to reveal a young man sitting at a table with a woman. The guard, wearing a dark blue uniform with a badge on his left chest, unlocks the cell door with a key held in his right hand and pulls it open; he has short brown hair, light skin, and a neutral expression. The young man, wearing a black and white striped shirt, sits at a table covered with a white tablecloth, facing the woman; he has short brown hair, light skin, and a neutral expression. The woman, wearing a dark blue shirt, sits opposite the young man, her face turned towards him; she has short blonde hair and light skin. The camera remains stationary, capturing the scene from a medium distance, positioned slightly to the right of the guard. The room is dimly lit, with a single light fixture illuminating the table and the two figures. The walls are made of large, grey concrete blocks, and a metal door is visible in the background. The scene is captured in real-life footage.example8A woman with blood on her face and a white tank top...A woman with blood on her face and a white tank top looks down and to her right, then back up as she speaks. She has dark hair pulled back, light skin, and her face and chest are covered in blood. The camera angle is a close-up, focused on the woman's face and upper torso. The lighting is dim and blue-toned, creating a somber and intense atmosphere. The scene appears to be from a movie or TV show.
example9A man with graying hair, a beard, and a gray shirt...A man with graying hair, a beard, and a gray shirt looks down and to his right, then turns his head to the left. The camera angle is a close-up, focused on the man's face. The lighting is dim, with a greenish tint. The scene appears to be real-life footage. Stepexample10A clear, turquoise river flows through a rocky canyon...A clear, turquoise river flows through a rocky canyon, cascading over a small waterfall and forming a pool of water at the bottom.The river is the main focus of the scene, with its clear water reflecting the surrounding trees and rocks. The canyon walls are steep and rocky, with some vegetation growing on them. The trees are mostly pine trees, with their green needles contrasting with the brown and gray rocks. The overall tone of the scene is one of peace and tranquility.example11A man in a suit enters a room and speaks to two women...A man in a suit enters a room and speaks to two women sitting on a couch. The man, wearing a dark suit with a gold tie, enters the room from the left and walks towards the center of the frame. He has short gray hair, light skin, and a serious expression. He places his right hand on the back of a chair as he approaches the couch. Two women are seated on a light-colored couch in the background. The woman on the left wears a light blue sweater and has short blonde hair. The woman on the right wears a white sweater and has short blonde hair. The camera remains stationary, focusing on the man as he enters the room. The room is brightly lit, with warm tones reflecting off the walls and furniture. The scene appears to be from a film or television show.example12The waves crash against the jagged rocks of the shoreline...The waves crash against the jagged rocks of the shoreline, sending spray high into the air.The rocks are a dark gray color, with sharp edges and deep crevices. The water is a clear blue-green, with white foam where the waves break against the rocks. The sky is a light gray, with a few white clouds dotting the horizon.
example13The camera pans across a cityscape of tall buildings...The camera pans across a cityscape of tall buildings with a circular building in the center. The camera moves from left to right, showing the tops of the buildings and the circular building in the center. The buildings are various shades of gray and white, and the circular building has a green roof. The camera angle is high, looking down at the city. The lighting is bright, with the sun shining from the upper left, casting shadows from the buildings. The scene is computer-generated imagery.example14A man walks towards a window, looks out, and then turns around...A man walks towards a window, looks out, and then turns around. He has short, dark hair, dark skin, and is wearing a brown coat over a red and gray scarf. He walks from left to right towards a window, his gaze fixed on something outside. The camera follows him from behind at a medium distance. The room is brightly lit, with white walls and a large window covered by a white curtain. As he approaches the window, he turns his head slightly to the left, then back to the right. He then turns his entire body to the right, facing the window. The camera remains stationary as he stands in front of the window. The scene is captured in real-life footage.example15Two police officers in dark blue uniforms and matching hats...Two police officers in dark blue uniforms and matching hats enter a dimly lit room through a doorway on the left side of the frame. The first officer, with short brown hair and a mustache, steps inside first, followed by his partner, who has a shaved head and a goatee. Both officers have serious expressions and maintain a steady pace as they move deeper into the room. The camera remains stationary, capturing them from a slightly low angle as they enter. The room has exposed brick walls and a corrugated metal ceiling, with a barred window visible in the background. The lighting is low-key, casting shadows on the officers' faces and emphasizing the grim atmosphere. The scene appears to be from a film or television show.example16A woman with short brown hair, wearing a maroon sleeveless top...A woman with short brown hair, wearing a maroon sleeveless top and a silver necklace, walks through a room while talking, then a woman with pink hair and a white shirt appears in the doorway and yells. The first woman walks from left to right, her expression serious; she has light skin and her eyebrows are slightly furrowed. The second woman stands in the doorway, her mouth open in a yell; she has light skin and her eyes are wide. The room is dimly lit, with a bookshelf visible in the background. The camera follows the first woman as she walks, then cuts to a close-up of the second woman's face. The scene is captured in real-life footage.

Models

ModelVersionNotesinference.py configComfyUI workflow (Recommended)
ltxv-13b0.9.7Highest quality, requires more VRAMltxv-13b-0.9.7-dev.yamlltxv-13b-i2v-base.json
ltxv-13b-fp80.9.7Quantized modelComing soonltxv-13b-i2v-base-fp8.json
ltxv-2b0.9.6Good quality, lower VRAM requirement than ltxv-13bltxv-2b-0.9.6-dev.yamlltxvideo-i2v.json
ltxv-2b-distilled0.9.615× faster, real-time capable, fewer steps needed, no STG/CFG requiredltxv-2b-0.9.6-distilled.yamlltxvideo-i2v-distilled.json

Model Details

  • Developed by: Lightricks
  • Model type: Diffusion-based text-to-video and image-to-video generation model
  • Language(s): English

Usage

Direct use

You can use the model for purposes under the license:

General tips:

  • The model works on resolutions that are divisible by 32 and number of frames that are divisible by 8 + 1 (e.g. 257). In case the resolution or number of frames are not divisible by 32 or 8 + 1, the input will be padded with -1 and then cropped to the desired resolution and number of frames.
  • The model works best on resolutions under 720 x 1280 and number of frames below 257.
  • Prompts should be in English. The more elaborate the better. Good prompt looks like The turquoise waves crash against the dark, jagged rocks of the shore, sending white foam spraying into the air. The scene is dominated by the stark contrast between the bright blue water and the dark, almost black rocks. The water is a clear, turquoise color, and the waves are capped with white foam. The rocks are dark and jagged, and they are covered in patches of green moss. The shore is lined with lush green vegetation, including trees and bushes. In the background, there are rolling hills covered in dense forest. The sky is cloudy, and the light is dim.

Online demo

The model is accessible right away via the following links:

ComfyUI

To use our model with ComfyUI, please follow the instructions at a dedicated ComfyUI repo.

Run locally

Installation

The codebase was tested with Python 3.10.5, CUDA version 12.2, and supports PyTorch >= 2.1.2.

git clone https://github.com/Lightricks/LTX-Video.git
cd LTX-Video

# create env
python -m venv env
source env/bin/activate
python -m pip install -e .\[inference-script\]

Inference

To use our model, please follow the inference code in inference.py:

For text-to-video generation:
python inference.py --prompt "PROMPT" --height HEIGHT --width WIDTH --num_frames NUM_FRAMES --seed SEED --pipeline_config ltxv-13b-0.9.7-dev.yaml
For image-to-video generation:
python inference.py --prompt "PROMPT" --input_image_path IMAGE_PATH --height HEIGHT --width WIDTH --num_frames NUM_FRAMES --seed SEED --pipeline_config ltxv-13b-0.9.7-dev.yaml

Diffusers 🧨

LTX Video is compatible with the Diffusers Python library. It supports both text-to-video and image-to-video generation.

Make sure you install diffusers before trying out the examples below.

pip install -U git+https://github.com/huggingface/diffusers

Now, you can run the examples below:

import torch
from diffusers import LTXPipeline
from diffusers.utils import export_to_video

pipe = LTXPipeline.from_pretrained("Lightricks/LTX-Video", torch_dtype=torch.bfloat16)
pipe.to("cuda")

prompt = "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage"
negative_prompt = "worst quality, inconsistent motion, blurry, jittery, distorted"

video = pipe(
    prompt=prompt,
    negative_prompt=negative_prompt,
    width=704,
    height=480,
    num_frames=161,
    num_inference_steps=50,
).frames[0]
export_to_video(video, "output.mp4", fps=24)

For image-to-video:

import torch
from diffusers import LTXImageToVideoPipeline
from diffusers.utils import export_to_video, load_image

pipe = LTXImageToVideoPipeline.from_pretrained("Lightricks/LTX-Video", torch_dtype=torch.bfloat16)
pipe.to("cuda")

image = load_image(
    "https://huggingface.co/datasets/a-r-r-o-w/tiny-meme-dataset-captioned/resolve/main/images/8.png"
)
prompt = "A young girl stands calmly in the foreground, looking directly at the camera, as a house fire rages in the background. Flames engulf the structure, with smoke billowing into the air. Firefighters in protective gear rush to the scene, a fire truck labeled '38' visible behind them. The girl's neutral expression contrasts sharply with the chaos of the fire, creating a poignant and emotionally charged scene."
negative_prompt = "worst quality, inconsistent motion, blurry, jittery, distorted"

video = pipe(
    image=image,
    prompt=prompt,
    negative_prompt=negative_prompt,
    width=704,
    height=480,
    num_frames=161,
    num_inference_steps=50,
).frames[0]
export_to_video(video, "output.mp4", fps=24)

To learn more, check out the official documentation.

Diffusers also supports directly loading from the original LTX checkpoints using the from_single_file() method. Check out this section to learn more.

Limitations

  • This model is not intended or able to provide factual information.
  • As a statistical model this checkpoint might amplify existing societal biases.
  • The model may fail to generate videos that matches the prompts perfectly.
  • Prompt following is heavily influenced by the prompting-style.

Как запустить

На своей GPU в ailist. Цена — по текущим предложениям провайдеров

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