LTX.io
comfyui
quantization
int4
convrot
diffusion
image-generation
video-generation
upscaling
krea
seedvr2
Instructions to use Winnougan/INT4-Convrot-Comfy-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use Winnougan/INT4-Convrot-Comfy-Models with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download Winnougan/INT4-Convrot-Comfy-Models --local-dir models/INT4-Convrot-Comfy-Models hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/INT4-Convrot-Comfy-Models/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/INT4-Convrot-Comfy-Models/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/INT4-Convrot-Comfy-Models/<checkpoint>.safetensors \ --distilled-lora models/INT4-Convrot-Comfy-Models/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/INT4-Convrot-Comfy-Models/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
BF16 Confusion
#10
by QrusherZA - opened
Hey, i just need some clarity around this one because i dont quiet understand it, so BF16 is not supported on Ampere (RTX 3080 in my case, so its emulated), the weights precision is still BF16, just wondering if it should not have been converted to FP16 first then to int8/int4 convrot.
I always convert BF16 to INT8 and INT4, nothing less than BF16. If you try to quantize FP8, the results will be quite poor
BF16 and FP16 are natively supported on Ampere, just not FP8 or NVFP4. They are "supported" insomuch as they'll work, but they'll be upcast to FP16.
Winnougan changed discussion status to closed