Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use vidfom/Ltx-3 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -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 serve -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
- Atomic Chat
File size: 5,330 Bytes
e00eceb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 | from __future__ import annotations
import os
import folder_paths
import glob
from aiohttp import web
import json
import logging
from functools import lru_cache
from utils.json_util import merge_json_recursive
# Extra locale files to load into main.json
EXTRA_LOCALE_FILES = [
"nodeDefs.json",
"commands.json",
"settings.json",
]
def safe_load_json_file(file_path: str) -> dict:
if not os.path.exists(file_path):
return {}
try:
with open(file_path, "r", encoding="utf-8") as f:
return json.load(f)
except json.JSONDecodeError:
logging.error(f"Error loading {file_path}")
return {}
class CustomNodeManager:
@lru_cache(maxsize=1)
def build_translations(self):
"""Load all custom nodes translations during initialization. Translations are
expected to be loaded from `locales/` folder.
The folder structure is expected to be the following:
- custom_nodes/
- custom_node_1/
- locales/
- en/
- main.json
- commands.json
- settings.json
returned translations are expected to be in the following format:
{
"en": {
"nodeDefs": {...},
"commands": {...},
"settings": {...},
...{other main.json keys}
}
}
"""
translations = {}
for folder in folder_paths.get_folder_paths("custom_nodes"):
# Sort glob results for deterministic ordering
for custom_node_dir in sorted(glob.glob(os.path.join(folder, "*/"))):
locales_dir = os.path.join(custom_node_dir, "locales")
if not os.path.exists(locales_dir):
continue
for lang_dir in glob.glob(os.path.join(locales_dir, "*/")):
lang_code = os.path.basename(os.path.dirname(lang_dir))
if lang_code not in translations:
translations[lang_code] = {}
# Load main.json
main_file = os.path.join(lang_dir, "main.json")
node_translations = safe_load_json_file(main_file)
# Load extra locale files
for extra_file in EXTRA_LOCALE_FILES:
extra_file_path = os.path.join(lang_dir, extra_file)
key = extra_file.split(".")[0]
json_data = safe_load_json_file(extra_file_path)
if json_data:
node_translations[key] = json_data
if node_translations:
translations[lang_code] = merge_json_recursive(
translations[lang_code], node_translations
)
return translations
def add_routes(self, routes, webapp, loadedModules):
example_workflow_folder_names = ["example_workflows", "example", "examples", "workflow", "workflows"]
@routes.get("/workflow_templates")
async def get_workflow_templates(request):
"""Returns a web response that contains the map of custom_nodes names and their associated workflow templates. The ones without templates are omitted."""
files = []
for folder in folder_paths.get_folder_paths("custom_nodes"):
for folder_name in example_workflow_folder_names:
pattern = os.path.join(folder, f"*/{folder_name}/*.json")
matched_files = glob.glob(pattern)
files.extend(matched_files)
workflow_templates_dict = (
{}
) # custom_nodes folder name -> example workflow names
for file in files:
custom_nodes_name = os.path.basename(
os.path.dirname(os.path.dirname(file))
)
workflow_name = os.path.splitext(os.path.basename(file))[0]
workflow_templates_dict.setdefault(custom_nodes_name, []).append(
workflow_name
)
return web.json_response(workflow_templates_dict)
# Serve workflow templates from custom nodes.
for module_name, module_dir in loadedModules:
for folder_name in example_workflow_folder_names:
workflows_dir = os.path.join(module_dir, folder_name)
if os.path.exists(workflows_dir):
if folder_name != "example_workflows":
logging.debug(
"Found example workflow folder '%s' for custom node '%s', consider renaming it to 'example_workflows'",
folder_name, module_name)
webapp.add_routes(
[
web.static(
"/api/workflow_templates/" + module_name, workflows_dir
)
]
)
@routes.get("/i18n")
async def get_i18n(request):
"""Returns translations from all custom nodes' locales folders."""
return web.json_response(self.build_translations())
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