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
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: 3,566 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 | import io
from comfy_api.input_impl.video_types import (
container_to_output_format,
get_open_write_kwargs,
)
from comfy_api.util import VideoContainer
def test_container_to_output_format_empty_string():
"""Test that an empty string input returns None. `None` arg allows default auto-detection."""
assert container_to_output_format("") is None
def test_container_to_output_format_none():
"""Test that None input returns None."""
assert container_to_output_format(None) is None
def test_container_to_output_format_comma_separated():
"""Test that a comma-separated list returns a valid singular format from the list."""
comma_separated_format = "mp4,mov,m4a"
output_format = container_to_output_format(comma_separated_format)
assert output_format in comma_separated_format
def test_container_to_output_format_single():
"""Test that a single format string (not comma-separated list) is returned as is."""
assert container_to_output_format("mp4") == "mp4"
def test_get_open_write_kwargs_filepath_no_format():
"""Test that 'format' kwarg is NOT set when dest is a file path."""
kwargs_auto = get_open_write_kwargs("output.mp4", "mp4", VideoContainer.AUTO)
assert "format" not in kwargs_auto, "Format should not be set for file paths (AUTO)"
kwargs_specific = get_open_write_kwargs("output.avi", "mp4", "avi")
fail_msg = "Format should not be set for file paths (Specific)"
assert "format" not in kwargs_specific, fail_msg
def test_get_open_write_kwargs_base_options_mode():
"""Test basic kwargs for file path: mode and movflags."""
kwargs = get_open_write_kwargs("output.mp4", "mp4", VideoContainer.AUTO)
assert kwargs["mode"] == "w", "mode should be set to write"
fail_msg = "movflags should be set to preserve custom metadata tags"
assert "movflags" in kwargs["options"], fail_msg
assert kwargs["options"]["movflags"] == "use_metadata_tags", fail_msg
def test_get_open_write_kwargs_bytesio_auto_format():
"""Test kwargs for BytesIO dest with AUTO format."""
dest = io.BytesIO()
container_fmt = "mov,mp4,m4a"
kwargs = get_open_write_kwargs(dest, container_fmt, VideoContainer.AUTO)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = (
"Format should be a valid format from the container's format list when AUTO"
)
assert kwargs["format"] in container_fmt, fail_msg
def test_get_open_write_kwargs_bytesio_specific_format():
"""Test kwargs for BytesIO dest with a specific single format."""
dest = io.BytesIO()
container_fmt = "avi"
to_fmt = VideoContainer.MP4
kwargs = get_open_write_kwargs(dest, container_fmt, to_fmt)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = "Format should be the specified format (lowercased) when output format is not AUTO"
assert kwargs["format"] == "mp4", fail_msg
def test_get_open_write_kwargs_bytesio_specific_format_list():
"""Test kwargs for BytesIO dest with a specific comma-separated format."""
dest = io.BytesIO()
container_fmt = "avi"
to_fmt = "mov,mp4,m4a" # A format string that is a list
kwargs = get_open_write_kwargs(dest, container_fmt, to_fmt)
assert kwargs["mode"] == "w"
assert kwargs["options"]["movflags"] == "use_metadata_tags"
fail_msg = "Format should be a valid format from the specified format list when output format is not AUTO"
assert kwargs["format"] in to_fmt, fail_msg
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