Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use vidfom/Ltx-3 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vidfom/Ltx-3", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-qat-UD-Q4_K_XL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use vidfom/Ltx-3 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use Docker
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use vidfom/Ltx-3 with Ollama:
ollama run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Unsloth Studio new
How to use vidfom/Ltx-3 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 vidfom/Ltx-3 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 vidfom/Ltx-3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vidfom/Ltx-3 to start chatting
- Docker Model Runner
How to use vidfom/Ltx-3 with Docker Model Runner:
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Lemonade
How to use vidfom/Ltx-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vidfom/Ltx-3:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Ltx-3-UD-Q4_K_XL
List all available models
lemonade list
| import json | |
| import os | |
| import folder_paths | |
| import server | |
| from .utils import find_tags | |
| class easyModelManager: | |
| def __init__(self): | |
| self.img_suffixes = [".png", ".jpg", ".jpeg", ".gif", ".webp", ".bmp", ".tiff", ".svg", ".tif", ".tiff"] | |
| self.default_suffixes = [".ckpt", ".pt", ".bin", ".pth", ".safetensors"] | |
| self.models_config = { | |
| "checkpoints": {"suffix": self.default_suffixes}, | |
| "loras": {"suffix": self.default_suffixes}, | |
| "unet": {"suffix": self.default_suffixes}, | |
| } | |
| self.model_lists = {} | |
| def find_thumbnail(self, model_type, name): | |
| file_no_ext = os.path.splitext(name)[0] | |
| for ext in self.img_suffixes: | |
| full_path = folder_paths.get_full_path(model_type, file_no_ext + ext) | |
| if os.path.isfile(str(full_path)): | |
| return full_path | |
| return None | |
| def get_model_lists(self, model_type): | |
| if model_type not in self.models_config: | |
| return [] | |
| filenames = folder_paths.get_filename_list(model_type) | |
| model_lists = [] | |
| for name in filenames: | |
| model_suffix = os.path.splitext(name)[-1] | |
| if model_suffix not in self.models_config[model_type]["suffix"]: | |
| continue | |
| else: | |
| cfg = { | |
| "name": os.path.basename(os.path.splitext(name)[0]), | |
| "full_name": name, | |
| "remark": '', | |
| "file_path": folder_paths.get_full_path(model_type, name), | |
| "type": model_type, | |
| "suffix": model_suffix, | |
| "dir_tags": find_tags(name), | |
| "cover": self.find_thumbnail(model_type, name), | |
| "metadata": None, | |
| "sha256": None | |
| } | |
| model_lists.append(cfg) | |
| return model_lists | |
| def get_model_info(self, model_type, model_name): | |
| pass | |
| # if __name__ == "__main__": | |
| # manager = easyModelManager() | |
| # print(manager.get_model_lists("checkpoints")) |