Instructions to use qwecja/ltx-ugc-bundle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use qwecja/ltx-ugc-bundle 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 qwecja/ltx-ugc-bundle --local-dir models/ltx-ugc-bundle 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/ltx-ugc-bundle/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/ltx-ugc-bundle/<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/ltx-ugc-bundle/<checkpoint>.safetensors \ --distilled-lora models/ltx-ugc-bundle/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/ltx-ugc-bundle/<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
| import json | |
| import os | |
| import re | |
| from typing import Union | |
| class AnyType(str): | |
| """A special class that is always equal in not equal comparisons. Credit to pythongosssss""" | |
| def __ne__(self, __value: object) -> bool: | |
| return False | |
| class FlexibleOptionalInputType(dict): | |
| """A special class to make flexible nodes that pass data to our python handlers. | |
| Enables both flexible/dynamic input types (like for Any Switch) or a dynamic number of inputs | |
| (like for Any Switch, Context Switch, Context Merge, Power Lora Loader, etc). | |
| Initially, ComfyUI only needed to return True for `__contains__` below, which told ComfyUI that | |
| our node will handle the input, regardless of what it is. | |
| However, after https://github.com/comfyanonymous/ComfyUI/pull/2666 ComdyUI's execution changed | |
| also checking the data for the key; specifcially, the type which is the first tuple entry. This | |
| type is supplied to our FlexibleOptionalInputType and returned for any non-data key. This can be a | |
| real type, or use the AnyType for additional flexibility. | |
| """ | |
| def __init__(self, type, data: Union[dict, None] = None): | |
| """Initializes the FlexibleOptionalInputType. | |
| Args: | |
| type: The flexible type to use when ComfyUI retrieves an unknown key (via `__getitem__`). | |
| data: An optional dict to use as the basis. This is stored both in a `data` attribute, so we | |
| can look it up without hitting our overrides, as well as iterated over and adding its key | |
| and values to our `self` keys. This way, when looked at, we will appear to represent this | |
| data. When used in an "optional" INPUT_TYPES, these are the starting optional node types. | |
| """ | |
| self.type = type | |
| self.data = data | |
| if self.data is not None: | |
| for k, v in self.data.items(): | |
| self[k] = v | |
| def __getitem__(self, key): | |
| # If we have this key in the initial data, then return it. Otherwise return the tuple with our | |
| # flexible type. | |
| if self.data is not None and key in self.data: | |
| val = self.data[key] | |
| return val | |
| return (self.type,) | |
| def __contains__(self, key): | |
| """Always contain a key, and we'll always return the tuple above when asked for it.""" | |
| return True | |
| any_type = AnyType("*") | |
| def is_dict_value_falsy(data: dict, dict_key: str): | |
| """Checks if a dict value is falsy.""" | |
| val = get_dict_value(data, dict_key) | |
| return not val | |
| def get_dict_value(data: dict, dict_key: str, default=None): | |
| """Gets a deeply nested value given a dot-delimited key.""" | |
| keys = dict_key.split('.') | |
| key = keys.pop(0) if len(keys) > 0 else None | |
| found = data[key] if key in data else None | |
| if found is not None and len(keys) > 0: | |
| return get_dict_value(found, '.'.join(keys), default) | |
| return found if found is not None else default | |
| def set_dict_value(data: dict, dict_key: str, value, create_missing_objects=True): | |
| """Sets a deeply nested value given a dot-delimited key.""" | |
| keys = dict_key.split('.') | |
| key = keys.pop(0) if len(keys) > 0 else None | |
| if key not in data: | |
| if create_missing_objects is False: | |
| return data | |
| data[key] = {} | |
| if len(keys) == 0: | |
| data[key] = value | |
| else: | |
| set_dict_value(data[key], '.'.join(keys), value, create_missing_objects) | |
| return data | |
| def dict_has_key(data: dict, dict_key): | |
| """Checks if a dict has a deeply nested dot-delimited key.""" | |
| keys = dict_key.split('.') | |
| key = keys.pop(0) if len(keys) > 0 else None | |
| if key is None or key not in data: | |
| return False | |
| if len(keys) == 0: | |
| return True | |
| return dict_has_key(data[key], '.'.join(keys)) | |
| def load_json_file(file: str, default=None): | |
| """Reads a json file and returns the json dict, stripping out "//" comments first.""" | |
| if path_exists(file): | |
| with open(file, 'r', encoding='UTF-8') as file: | |
| config = file.read() | |
| try: | |
| return json.loads(config) | |
| except json.decoder.JSONDecodeError: | |
| try: | |
| config = re.sub(r"^\s*//\s.*", "", config, flags=re.MULTILINE) | |
| return json.loads(config) | |
| except json.decoder.JSONDecodeError: | |
| try: | |
| config = re.sub(r"(?:^|\s)//.*", "", config, flags=re.MULTILINE) | |
| return json.loads(config) | |
| except json.decoder.JSONDecodeError: | |
| pass | |
| return default | |
| def save_json_file(file_path: str, data: dict): | |
| """Saves a json file.""" | |
| os.makedirs(os.path.dirname(file_path), exist_ok=True) | |
| with open(file_path, 'w+', encoding='UTF-8') as file: | |
| json.dump(data, file, sort_keys=False, indent=2, separators=(",", ": ")) | |
| def path_exists(path): | |
| """Checks if a path exists, accepting None type.""" | |
| if path is not None: | |
| return os.path.exists(path) | |
| return False | |
| def file_exists(path): | |
| """Checks if a file exists, accepting None type.""" | |
| if path is not None: | |
| return os.path.isfile(path) | |
| return False | |
| def remove_path(path): | |
| """Removes a path, if it exists.""" | |
| if path_exists(path): | |
| os.remove(path) | |
| return True | |
| return False | |
| def abspath(file_path: str): | |
| """Resolves the abspath of a file, resolving symlinks and user dirs.""" | |
| abs_path = os.path.abspath(file_path) if file_path else file_path | |
| if abs_path and not path_exists(abs_path): | |
| maybe_path = os.path.abspath(os.path.realpath(os.path.expanduser(file_path))) | |
| abs_path = maybe_path if path_exists(maybe_path) else abs_path | |
| return abs_path | |
| def sub_abspath(parent_dir: str, rel_path: str): | |
| """Resolves the abspath under a parent directory ensuring it exists and is contained within.""" | |
| rel_path = os.path.join(parent_dir, rel_path) | |
| abs_path = abspath(rel_path) | |
| if not path_exists(abs_path) or not abs_path.startswith(parent_dir): | |
| return None | |
| return abs_path | |
| class ByPassTypeTuple(tuple): | |
| """A special class that will return additional "AnyType" strings beyond defined values. | |
| Credit to Trung0246 | |
| """ | |
| def __getitem__(self, index): | |
| if index > len(self) - 1: | |
| return AnyType("*") | |
| return super().__getitem__(index) | |