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
| 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: | |
| 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) | |