Model reference · open weights
LTX-Video-0.9.1 is an open-weight video model from a-r-r-o-w. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | a-r-r-o-w |
|---|---|
| Type | Video models |
| Task | Text→video |
| Parameters (lead) | 1.9B |
| Runs with | diffusers |
| Released | 2024-12-22 |
| Popularity | 505 downloads / month |
| Licence | Unknown |
About
Unofficial Diffusers-format weights for https://huggingface.co/Lightricks/LTX-Video (version 0.9.1).
Text-to-Video:
import torch
from diffusers import LTXPipeline
from diffusers.utils import export_to_video
pipe = LTXPipeline.from_pretrained("a-r-r-o-w/LTX-Video-0.9.1-diffusers", 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,
decode_timestep=0.03,
decode_noise_scale=0.025,
).frames[0]
export_to_video(video, "output.mp4", fps=24)
Image-to-Video:
import torch
from diffusers import LTXImageToVideoPipeline
from diffusers.utils import export_to_video, load_image
pipe = LTXImageToVideoPipeline.from_pretrained("a-r-r-o-w/LTX-Video-0.9.1-diffusers", 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,
decode_timestep=0.03,
decode_noise_scale=0.025,
).frames[0]
export_to_video(video, "output.mp4", fps=24)
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys ltx-video-0-9-1 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (ltx-video-0-9-1 below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/videos/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"ltx-video-0-9-1","prompt":"a drone shot over a forest"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.