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
| from __future__ import annotations | |
| from typing import TypedDict | |
| import os | |
| import folder_paths | |
| import glob | |
| from aiohttp import web | |
| import hashlib | |
| class Source: | |
| custom_node = "custom_node" | |
| templates = "templates" | |
| class SubgraphEntry(TypedDict): | |
| source: str | |
| """ | |
| Source of subgraph - custom_nodes vs templates. | |
| """ | |
| path: str | |
| """ | |
| Relative path of the subgraph file. | |
| For custom nodes, will be the relative directory like <custom_node_dir>/subgraphs/<name>.json | |
| """ | |
| name: str | |
| """ | |
| Name of subgraph file. | |
| """ | |
| info: CustomNodeSubgraphEntryInfo | |
| """ | |
| Additional info about subgraph; in the case of custom_nodes, will contain nodepack name | |
| """ | |
| data: str | |
| class CustomNodeSubgraphEntryInfo(TypedDict): | |
| node_pack: str | |
| """Node pack name.""" | |
| class SubgraphManager: | |
| def __init__(self): | |
| self.cached_custom_node_subgraphs: dict[SubgraphEntry] | None = None | |
| self.cached_blueprint_subgraphs: dict[SubgraphEntry] | None = None | |
| def _create_entry(self, file: str, source: str, node_pack: str) -> tuple[str, SubgraphEntry]: | |
| """Create a subgraph entry from a file path. Expects normalized path (forward slashes).""" | |
| entry_id = hashlib.sha256(f"{source}{file}".encode()).hexdigest() | |
| entry: SubgraphEntry = { | |
| "source": source, | |
| "name": os.path.splitext(os.path.basename(file))[0], | |
| "path": file, | |
| "info": {"node_pack": node_pack}, | |
| } | |
| return entry_id, entry | |
| async def load_entry_data(self, entry: SubgraphEntry): | |
| with open(entry['path'], 'r', encoding='utf-8') as f: | |
| entry['data'] = f.read() | |
| return entry | |
| async def sanitize_entry(self, entry: SubgraphEntry | None, remove_data=False) -> SubgraphEntry | None: | |
| if entry is None: | |
| return None | |
| entry = entry.copy() | |
| entry.pop('path', None) | |
| if remove_data: | |
| entry.pop('data', None) | |
| return entry | |
| async def sanitize_entries(self, entries: dict[str, SubgraphEntry], remove_data=False) -> dict[str, SubgraphEntry]: | |
| entries = entries.copy() | |
| for key in list(entries.keys()): | |
| entries[key] = await self.sanitize_entry(entries[key], remove_data) | |
| return entries | |
| async def get_custom_node_subgraphs(self, loadedModules, force_reload=False): | |
| """Load subgraphs from custom nodes.""" | |
| if not force_reload and self.cached_custom_node_subgraphs is not None: | |
| return self.cached_custom_node_subgraphs | |
| subgraphs_dict: dict[SubgraphEntry] = {} | |
| for folder in folder_paths.get_folder_paths("custom_nodes"): | |
| pattern = os.path.join(folder, "*/subgraphs/*.json") | |
| for file in glob.glob(pattern): | |
| file = file.replace('\\', '/') | |
| node_pack = "custom_nodes." + file.split('/')[-3] | |
| entry_id, entry = self._create_entry(file, Source.custom_node, node_pack) | |
| subgraphs_dict[entry_id] = entry | |
| self.cached_custom_node_subgraphs = subgraphs_dict | |
| return subgraphs_dict | |
| async def get_blueprint_subgraphs(self, force_reload=False): | |
| """Load subgraphs from the blueprints directory.""" | |
| if not force_reload and self.cached_blueprint_subgraphs is not None: | |
| return self.cached_blueprint_subgraphs | |
| subgraphs_dict: dict[SubgraphEntry] = {} | |
| blueprints_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'blueprints') | |
| if os.path.exists(blueprints_dir): | |
| for file in glob.glob(os.path.join(blueprints_dir, "*.json")): | |
| file = file.replace('\\', '/') | |
| entry_id, entry = self._create_entry(file, Source.templates, "comfyui") | |
| subgraphs_dict[entry_id] = entry | |
| self.cached_blueprint_subgraphs = subgraphs_dict | |
| return subgraphs_dict | |
| async def get_all_subgraphs(self, loadedModules, force_reload=False): | |
| """Get all subgraphs from all sources (custom nodes and blueprints).""" | |
| custom_node_subgraphs = await self.get_custom_node_subgraphs(loadedModules, force_reload) | |
| blueprint_subgraphs = await self.get_blueprint_subgraphs(force_reload) | |
| return {**custom_node_subgraphs, **blueprint_subgraphs} | |
| async def get_subgraph(self, id: str, loadedModules): | |
| """Get a specific subgraph by ID from any source.""" | |
| entry = (await self.get_all_subgraphs(loadedModules)).get(id) | |
| if entry is not None and entry.get('data') is None: | |
| await self.load_entry_data(entry) | |
| return entry | |
| def add_routes(self, routes, loadedModules): | |
| async def get_global_subgraphs(request): | |
| subgraphs_dict = await self.get_all_subgraphs(loadedModules) | |
| return web.json_response(await self.sanitize_entries(subgraphs_dict, remove_data=True)) | |
| async def get_global_subgraph(request): | |
| id = request.match_info.get("id", None) | |
| subgraph = await self.get_subgraph(id, loadedModules) | |
| return web.json_response(await self.sanitize_entry(subgraph)) | |