Instructions to use hgjc/ltx-ugc-bundle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use hgjc/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 hgjc/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 random | |
| import server | |
| from enum import Enum | |
| class SGmode(Enum): | |
| FIX = 1 | |
| INCR = 2 | |
| DECR = 3 | |
| RAND = 4 | |
| class SeedGenerator: | |
| def __init__(self, base_value, action): | |
| self.base_value = base_value | |
| if action == "fixed" or action == "increment" or action == "decrement" or action == "randomize": | |
| self.action = SGmode.FIX | |
| elif action == 'increment for each node': | |
| self.action = SGmode.INCR | |
| elif action == 'decrement for each node': | |
| self.action = SGmode.DECR | |
| elif action == 'randomize for each node': | |
| self.action = SGmode.RAND | |
| def next(self): | |
| seed = self.base_value | |
| if self.action == SGmode.INCR: | |
| self.base_value += 1 | |
| if self.base_value > 1125899906842624: | |
| self.base_value = 0 | |
| elif self.action == SGmode.DECR: | |
| self.base_value -= 1 | |
| if self.base_value < 0: | |
| self.base_value = 1125899906842624 | |
| elif self.action == SGmode.RAND: | |
| self.base_value = random.randint(0, 1125899906842624) | |
| return seed | |
| def control_seed(v, action, seed_is_global): | |
| action = v['inputs']['action'] if seed_is_global else action | |
| value = v['inputs']['value'] if seed_is_global else v['inputs']['seed_num'] | |
| if action == 'increment' or action == 'increment for each node': | |
| value = value + 1 | |
| if value > 1125899906842624: | |
| value = 0 | |
| elif action == 'decrement' or action == 'decrement for each node': | |
| value = value - 1 | |
| if value < 0: | |
| value = 1125899906842624 | |
| elif action == 'randomize' or action == 'randomize for each node': | |
| value = random.randint(0, 1125899906842624) | |
| if seed_is_global: | |
| v['inputs']['value'] = value | |
| return value | |
| def prompt_seed_update(json_data): | |
| try: | |
| seed_widget_map = json_data['extra_data']['extra_pnginfo']['workflow']['seed_widgets'] | |
| except: | |
| return None | |
| workflow = json_data['extra_data']['extra_pnginfo']['workflow'] | |
| seed_widget_map = workflow['seed_widgets'] | |
| value = None | |
| mode = None | |
| node = None | |
| action = None | |
| seed_is_global = False | |
| for k, v in json_data['prompt'].items(): | |
| if 'class_type' not in v: | |
| continue | |
| cls = v['class_type'] | |
| if cls == 'easy globalSeed': | |
| mode = v['inputs']['mode'] | |
| action = v['inputs']['action'] | |
| value = v['inputs']['value'] | |
| node = k, v | |
| seed_is_global = True | |
| # control before generated | |
| if mode is not None and mode and seed_is_global: | |
| value = control_seed(node[1], action, seed_is_global) | |
| if seed_is_global: | |
| if value is not None: | |
| seed_generator = SeedGenerator(value, action) | |
| for k, v in json_data['prompt'].items(): | |
| for k2, v2 in v['inputs'].items(): | |
| if isinstance(v2, str) and '$GlobalSeed.value$' in v2: | |
| v['inputs'][k2] = v2.replace('$GlobalSeed.value$', str(value)) | |
| if k not in seed_widget_map: | |
| continue | |
| if 'seed_num' in v['inputs']: | |
| if isinstance(v['inputs']['seed_num'], int): | |
| v['inputs']['seed_num'] = seed_generator.next() | |
| if 'seed' in v['inputs']: | |
| if isinstance(v['inputs']['seed'], int): | |
| v['inputs']['seed'] = seed_generator.next() | |
| if 'noise_seed' in v['inputs']: | |
| if isinstance(v['inputs']['noise_seed'], int): | |
| v['inputs']['noise_seed'] = seed_generator.next() | |
| for k2, v2 in v['inputs'].items(): | |
| if isinstance(v2, str) and '$GlobalSeed.value$' in v2: | |
| v['inputs'][k2] = v2.replace('$GlobalSeed.value$', str(value)) | |
| # control after generated | |
| if mode is not None and not mode: | |
| control_seed(node[1], action, seed_is_global) | |
| return value is not None | |
| def workflow_seed_update(json_data): | |
| nodes = json_data['extra_data']['extra_pnginfo']['workflow']['nodes'] | |
| seed_widget_map = json_data['extra_data']['extra_pnginfo']['workflow']['seed_widgets'] | |
| prompt = json_data['prompt'] | |
| updated_seed_map = {} | |
| value = None | |
| for node in nodes: | |
| node_id = str(node['id']) | |
| if node_id in prompt: | |
| if node['type'] == 'easy globalSeed': | |
| value = prompt[node_id]['inputs']['value'] | |
| length = len(node['widgets_values']) | |
| node['widgets_values'][length-1] = node['widgets_values'][0] | |
| node['widgets_values'][0] = value | |
| elif node_id in seed_widget_map: | |
| widget_idx = seed_widget_map[node_id] | |
| if 'seed_num' in prompt[node_id]['inputs']: | |
| seed = prompt[node_id]['inputs']['seed_num'] | |
| elif 'noise_seed' in prompt[node_id]['inputs']: | |
| seed = prompt[node_id]['inputs']['noise_seed'] | |
| else: | |
| seed = prompt[node_id]['inputs']['seed'] | |
| node['widgets_values'][widget_idx] = seed | |
| updated_seed_map[node_id] = seed | |
| server.PromptServer.instance.send_sync("easyuse-global-seed", {"id": node_id, "value": value, "seed_map": updated_seed_map}) | |
| def onprompt(json_data): | |
| is_changed = prompt_seed_update(json_data) | |
| if is_changed: | |
| workflow_seed_update(json_data) | |
| return json_data | |
| server.PromptServer.instance.add_on_prompt_handler(onprompt) |