Image-to-Video
Diffusers
GGUF
text-to-video
video-to-video
image-text-to-video
audio-to-video
text-to-audio
video-to-audio
audio-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
ltx-2
ltx-2-3
ltx-video
ltxv
lightricks
sulphur
sulphur-2
Instructions to use vantagewithai/Sulphur-2-Base-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vantagewithai/Sulphur-2-Base-GGUF with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vantagewithai/Sulphur-2-Base-GGUF", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Quantized GGUF Versions of Sulphur 2 for ComfyUI
Original model Link: https://huggingface.co/SulphurAI/Sulphur-2-base
Watch us at Youtube: @VantageWithAI
Sulphur 2
An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats.
Credits
- (TenStrip) โ Testing & model merging (His i2v merge of sulphur 2, highly recommend for i2v)
- @s1lv3rc01n โ Testing & model merging/quantizing (silveroxides)
- @mov7162 โ Musubi Tuner guidance
- And many others, if you'd like to be on the credits and I didn't place you here, message me I likely assumed you didn't want to be here.
Funders
- Anonymous funder #1 โ Supported the original Sulphur
- Anonymous funder #2 โ Made Sulphur 2 possible; this model wouldn't exist without them
Thank you to everyone who contributed.
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