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 Settings
- 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
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
| """Test that Alembic migrations run cleanly on a file-backed SQLite DB. | |
| This catches problems like unnamed FK constraints that prevent batch-mode | |
| drop_constraint from working on real SQLite files (see MB-2). | |
| Migrations 0001 and 0002 are already shipped, so we only exercise | |
| upgrade/downgrade for 0003+. | |
| """ | |
| import os | |
| import pytest | |
| from alembic import command | |
| from alembic.config import Config | |
| # Oldest shipped revision — we upgrade to here as a baseline and never | |
| # downgrade past it. | |
| _BASELINE = "0002_merge_to_asset_references" | |
| def _make_config(db_path: str) -> Config: | |
| root = os.path.join(os.path.dirname(__file__), "../..") | |
| config_path = os.path.abspath(os.path.join(root, "alembic.ini")) | |
| scripts_path = os.path.abspath(os.path.join(root, "alembic_db")) | |
| cfg = Config(config_path) | |
| cfg.set_main_option("script_location", scripts_path) | |
| cfg.set_main_option("sqlalchemy.url", f"sqlite:///{db_path}") | |
| return cfg | |
| def migration_db(tmp_path): | |
| """Yield an alembic Config pre-upgraded to the baseline revision.""" | |
| db_path = str(tmp_path / "test_migration.db") | |
| cfg = _make_config(db_path) | |
| command.upgrade(cfg, _BASELINE) | |
| yield cfg | |
| def test_upgrade_to_head(migration_db): | |
| """Upgrade from baseline to head must succeed on a file-backed DB.""" | |
| command.upgrade(migration_db, "head") | |
| def test_downgrade_to_baseline(migration_db): | |
| """Upgrade to head then downgrade back to baseline.""" | |
| command.upgrade(migration_db, "head") | |
| command.downgrade(migration_db, _BASELINE) | |
| def test_upgrade_downgrade_cycle(migration_db): | |
| """Full cycle: upgrade → downgrade → upgrade again.""" | |
| command.upgrade(migration_db, "head") | |
| command.downgrade(migration_db, _BASELINE) | |
| command.upgrade(migration_db, "head") | |