Image-to-Video
GGUF
ggml
unsloth
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-video
ltxv
lightricks
Instructions to use unsloth/LTX-2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use unsloth/LTX-2-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/LTX-2-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unsloth/LTX-2-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/LTX-2-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unsloth/LTX-2-GGUF", max_seq_length=2048, )
If I have 16GB of VRAM, which Q should I choose?
#10
by Alfredo182 - opened
My setup is in my profile. I hope someone can answer me, I'm new to this.
You want to end up with at least 1GB free after loading all models. That leaves room for overhead. If you put your hardware in your profile, many model pages will show you what they think you can use. For instance, here are little pics of what it thinks I can get away with with my 16GB 5070Ti, my 32GB dual-5060Ti setup (If you want to know how I did this, look here: https://www.reddit.com/r/LocalLLaMA/comments/1r1qpdv/dual_rtx_5060_ti_32gb_pooled_vram_vs_single_rtx/), my 16GB Mac Pro, and my 8GB Jetson Nano - which it says can't run any of them. :( (But that's okay, it has other things to do. ;) )



