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
File size: 5,845 Bytes
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import os
import shutil
from app.logger import log_startup_warning
from utils.install_util import get_missing_requirements_message
from filelock import FileLock, Timeout
from comfy.cli_args import args
_DB_AVAILABLE = False
Session = None
try:
from alembic import command
from alembic.config import Config
from alembic.runtime.migration import MigrationContext
from alembic.script import ScriptDirectory
from sqlalchemy import create_engine, event
from sqlalchemy.orm import sessionmaker
from sqlalchemy.pool import StaticPool
from app.database.models import Base
import app.assets.database.models # noqa: F401 — register models with Base.metadata
_DB_AVAILABLE = True
except ImportError as e:
log_startup_warning(
f"""
------------------------------------------------------------------------
Error importing dependencies: {e}
{get_missing_requirements_message()}
This error is happening because ComfyUI now uses a local sqlite database.
------------------------------------------------------------------------
""".strip()
)
def dependencies_available():
"""
Temporary function to check if the dependencies are available
"""
return _DB_AVAILABLE
def can_create_session():
"""
Temporary function to check if the database is available to create a session
During initial release there may be environmental issues (or missing dependencies) that prevent the database from being created
"""
return dependencies_available() and Session is not None
def get_alembic_config():
root_path = os.path.join(os.path.dirname(__file__), "../..")
config_path = os.path.abspath(os.path.join(root_path, "alembic.ini"))
scripts_path = os.path.abspath(os.path.join(root_path, "alembic_db"))
config = Config(config_path)
config.set_main_option("script_location", scripts_path)
config.set_main_option("sqlalchemy.url", args.database_url)
return config
def get_db_path():
url = args.database_url
if url.startswith("sqlite:///"):
return url.split("///")[1]
else:
raise ValueError(f"Unsupported database URL '{url}'.")
_db_lock = None
def _acquire_file_lock(db_path):
"""Acquire an OS-level file lock to prevent multi-process access.
Uses filelock for cross-platform support (macOS, Linux, Windows).
The OS automatically releases the lock when the process exits, even on crashes.
"""
global _db_lock
lock_path = db_path + ".lock"
_db_lock = FileLock(lock_path)
try:
_db_lock.acquire(timeout=0)
except Timeout:
raise RuntimeError(
f"Could not acquire lock on database '{db_path}'. "
"Another ComfyUI process may already be using it. "
"Use --database-url to specify a separate database file."
)
def _is_memory_db(db_url):
"""Check if the database URL refers to an in-memory SQLite database."""
return db_url in ("sqlite:///:memory:", "sqlite://")
def init_db():
db_url = args.database_url
logging.debug(f"Database URL: {db_url}")
if _is_memory_db(db_url):
_init_memory_db(db_url)
else:
_init_file_db(db_url)
def _init_memory_db(db_url):
"""Initialize an in-memory SQLite database using metadata.create_all.
Alembic migrations don't work with in-memory SQLite because each
connection gets its own separate database — tables created by Alembic's
internal connection are lost immediately.
"""
engine = create_engine(
db_url,
poolclass=StaticPool,
connect_args={"check_same_thread": False},
)
@event.listens_for(engine, "connect")
def set_sqlite_pragma(dbapi_connection, connection_record):
cursor = dbapi_connection.cursor()
cursor.execute("PRAGMA foreign_keys=ON")
cursor.close()
Base.metadata.create_all(engine)
global Session
Session = sessionmaker(bind=engine)
def _init_file_db(db_url):
"""Initialize a file-backed SQLite database using Alembic migrations."""
db_path = get_db_path()
db_exists = os.path.exists(db_path)
config = get_alembic_config()
# Check if we need to upgrade
engine = create_engine(db_url)
# Enable foreign key enforcement for SQLite
@event.listens_for(engine, "connect")
def set_sqlite_pragma(dbapi_connection, connection_record):
cursor = dbapi_connection.cursor()
cursor.execute("PRAGMA foreign_keys=ON")
cursor.close()
conn = engine.connect()
context = MigrationContext.configure(conn)
current_rev = context.get_current_revision()
script = ScriptDirectory.from_config(config)
target_rev = script.get_current_head()
if target_rev is None:
logging.warning("No target revision found.")
elif current_rev != target_rev:
# Backup the database pre upgrade
backup_path = db_path + ".bkp"
if db_exists:
shutil.copy(db_path, backup_path)
else:
backup_path = None
try:
command.upgrade(config, target_rev)
logging.info(f"Database upgraded from {current_rev} to {target_rev}")
except Exception as e:
if backup_path:
# Restore the database from backup if upgrade fails
shutil.copy(backup_path, db_path)
os.remove(backup_path)
logging.exception("Error upgrading database: ")
raise e
# Acquire an OS-level file lock after migrations are complete.
# Alembic uses its own connection, so we must wait until it's done
# before locking — otherwise our own lock blocks the migration.
conn.close()
_acquire_file_lock(db_path)
global Session
Session = sessionmaker(bind=engine)
def create_session():
return Session()
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