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
| #!/usr/bin/env python3 | |
| """ | |
| Script to generate .pyi stub files for the synchronous API wrappers. | |
| This allows generating stubs without running the full ComfyUI application. | |
| """ | |
| import os | |
| import sys | |
| import logging | |
| import importlib | |
| # Add ComfyUI to path so we can import modules | |
| sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
| from comfy_api.internal.async_to_sync import AsyncToSyncConverter | |
| from comfy_api.version_list import supported_versions | |
| def generate_stubs_for_module(module_name: str) -> None: | |
| """Generate stub files for a specific module that exports ComfyAPI and ComfyAPISync.""" | |
| try: | |
| # Import the module | |
| module = importlib.import_module(module_name) | |
| # Check if module has ComfyAPISync (the sync wrapper) | |
| if hasattr(module, "ComfyAPISync"): | |
| # Module already has a sync class | |
| api_class = getattr(module, "ComfyAPI", None) | |
| sync_class = getattr(module, "ComfyAPISync") | |
| if api_class: | |
| # Generate the stub file | |
| AsyncToSyncConverter.generate_stub_file(api_class, sync_class) | |
| logging.info(f"Generated stub file for {module_name}") | |
| else: | |
| logging.warning( | |
| f"Module {module_name} has ComfyAPISync but no ComfyAPI" | |
| ) | |
| elif hasattr(module, "ComfyAPI"): | |
| # Module only has async API, need to create sync wrapper first | |
| from comfy_api.internal.async_to_sync import create_sync_class | |
| api_class = getattr(module, "ComfyAPI") | |
| sync_class = create_sync_class(api_class) | |
| # Generate the stub file | |
| AsyncToSyncConverter.generate_stub_file(api_class, sync_class) | |
| logging.info(f"Generated stub file for {module_name}") | |
| else: | |
| logging.warning( | |
| f"Module {module_name} does not export ComfyAPI or ComfyAPISync" | |
| ) | |
| except Exception as e: | |
| logging.error(f"Failed to generate stub for {module_name}: {e}") | |
| import traceback | |
| traceback.print_exc() | |
| def main(): | |
| """Main function to generate all API stub files.""" | |
| logging.basicConfig(level=logging.INFO) | |
| logging.info("Starting stub generation...") | |
| # Dynamically get module names from supported_versions | |
| api_modules = [] | |
| for api_class in supported_versions: | |
| # Extract module name from the class | |
| module_name = api_class.__module__ | |
| if module_name not in api_modules: | |
| api_modules.append(module_name) | |
| logging.info(f"Found {len(api_modules)} API modules: {api_modules}") | |
| # Generate stubs for each module | |
| for module_name in api_modules: | |
| generate_stubs_for_module(module_name) | |
| logging.info("Stub generation complete!") | |
| if __name__ == "__main__": | |
| main() | |