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 Settings
- 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
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: 6,036 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 | import math
import pytest
from collections import OrderedDict
from unittest.mock import patch, MagicMock
mock_nodes = MagicMock()
mock_nodes.MAX_RESOLUTION = 16384
mock_server = MagicMock()
with patch.dict("sys.modules", {"nodes": mock_nodes, "server": mock_server}):
from comfy_extras.nodes_math import MathExpressionNode
class TestMathExpressionExecute:
@staticmethod
def _exec(expression: str, **kwargs) -> object:
values = OrderedDict(kwargs)
return MathExpressionNode.execute(expression, values)
def test_addition(self):
result = self._exec("a + b", a=3, b=4)
assert result[0] == 7.0
assert result[1] == 7
def test_subtraction(self):
result = self._exec("a - b", a=10, b=3)
assert result[0] == 7.0
assert result[1] == 7
def test_multiplication(self):
result = self._exec("a * b", a=3, b=5)
assert result[0] == 15.0
assert result[1] == 15
def test_division(self):
result = self._exec("a / b", a=10, b=4)
assert result[0] == 2.5
assert result[1] == 2
def test_single_input(self):
result = self._exec("a * 2", a=5)
assert result[0] == 10.0
assert result[1] == 10
def test_three_inputs(self):
result = self._exec("a + b + c", a=1, b=2, c=3)
assert result[0] == 6.0
assert result[1] == 6
def test_float_inputs(self):
result = self._exec("a + b", a=1.5, b=2.5)
assert result[0] == 4.0
assert result[1] == 4
def test_mixed_int_float_inputs(self):
result = self._exec("a * b", a=1024, b=1.5)
assert result[0] == 1536.0
assert result[1] == 1536
def test_mixed_resolution_scale(self):
result = self._exec("a * b", a=512, b=0.75)
assert result[0] == 384.0
assert result[1] == 384
def test_sum_values_array(self):
result = self._exec("sum(values)", a=1, b=2, c=3)
assert result[0] == 6.0
def test_sum_variadic(self):
result = self._exec("sum(a, b, c)", a=1, b=2, c=3)
assert result[0] == 6.0
def test_min_values(self):
result = self._exec("min(values)", a=5, b=2, c=8)
assert result[0] == 2.0
def test_max_values(self):
result = self._exec("max(values)", a=5, b=2, c=8)
assert result[0] == 8.0
def test_abs_function(self):
result = self._exec("abs(a)", a=-7)
assert result[0] == 7.0
assert result[1] == 7
def test_sqrt(self):
result = self._exec("sqrt(a)", a=16)
assert result[0] == 4.0
assert result[1] == 4
def test_ceil(self):
result = self._exec("ceil(a)", a=2.3)
assert result[0] == 3.0
assert result[1] == 3
def test_floor(self):
result = self._exec("floor(a)", a=2.7)
assert result[0] == 2.0
assert result[1] == 2
def test_sin(self):
result = self._exec("sin(a)", a=0)
assert result[0] == 0.0
def test_log10(self):
result = self._exec("log10(a)", a=100)
assert result[0] == 2.0
assert result[1] == 2
def test_float_output_type(self):
result = self._exec("a + b", a=1, b=2)
assert isinstance(result[0], float)
def test_int_output_type(self):
result = self._exec("a + b", a=1, b=2)
assert isinstance(result[1], int)
def test_non_numeric_result_raises(self):
with pytest.raises(ValueError, match="must evaluate to a numeric result"):
self._exec("'hello'", a=42)
def test_undefined_function_raises(self):
with pytest.raises(Exception, match="not defined"):
self._exec("str(a)", a=42)
def test_boolean_result_raises(self):
with pytest.raises(ValueError, match="got bool"):
self._exec("a > b", a=5, b=3)
def test_empty_expression_raises(self):
with pytest.raises(ValueError, match="Expression cannot be empty"):
self._exec("", a=1)
def test_whitespace_only_expression_raises(self):
with pytest.raises(ValueError, match="Expression cannot be empty"):
self._exec(" ", a=1)
# --- Missing function coverage (round, pow, log, log2, cos, tan) ---
def test_round(self):
result = self._exec("round(a)", a=2.7)
assert result[0] == 3.0
assert result[1] == 3
def test_round_with_ndigits(self):
result = self._exec("round(a, 2)", a=3.14159)
assert result[0] == pytest.approx(3.14)
def test_pow(self):
result = self._exec("pow(a, b)", a=2, b=10)
assert result[0] == 1024.0
assert result[1] == 1024
def test_log(self):
result = self._exec("log(a)", a=math.e)
assert result[0] == pytest.approx(1.0)
def test_log2(self):
result = self._exec("log2(a)", a=8)
assert result[0] == pytest.approx(3.0)
def test_cos(self):
result = self._exec("cos(a)", a=0)
assert result[0] == 1.0
def test_tan(self):
result = self._exec("tan(a)", a=0)
assert result[0] == 0.0
# --- int/float converter functions ---
def test_int_converter(self):
result = self._exec("int(a / b)", a=7, b=2)
assert result[1] == 3
def test_float_converter(self):
result = self._exec("float(a)", a=5)
assert result[0] == 5.0
# --- Error path tests ---
def test_division_by_zero_raises(self):
with pytest.raises(ZeroDivisionError):
self._exec("a / b", a=1, b=0)
def test_sqrt_negative_raises(self):
with pytest.raises(ValueError, match="math domain error"):
self._exec("sqrt(a)", a=-1)
def test_overflow_inf_raises(self):
with pytest.raises(ValueError, match="non-finite result"):
self._exec("a * b", a=1e308, b=10)
def test_pow_huge_exponent_raises(self):
with pytest.raises(ValueError, match="Exponent .* exceeds maximum"):
self._exec("pow(a, b)", a=10, b=10000000)
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