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
File size: 4,000 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 | """Tests for feature flags functionality."""
from comfy_api.feature_flags import (
get_connection_feature,
supports_feature,
get_server_features,
SERVER_FEATURE_FLAGS,
)
class TestFeatureFlags:
"""Test suite for feature flags functions."""
def test_get_server_features_returns_copy(self):
"""Test that get_server_features returns a copy of the server flags."""
features = get_server_features()
# Verify it's a copy by modifying it
features["test_flag"] = True
# Original should be unchanged
assert "test_flag" not in SERVER_FEATURE_FLAGS
def test_get_server_features_contains_expected_flags(self):
"""Test that server features contain expected flags."""
features = get_server_features()
assert "supports_preview_metadata" in features
assert features["supports_preview_metadata"] is True
assert "max_upload_size" in features
assert isinstance(features["max_upload_size"], (int, float))
def test_get_connection_feature_with_missing_sid(self):
"""Test getting feature for non-existent session ID."""
sockets_metadata = {}
result = get_connection_feature(sockets_metadata, "missing_sid", "some_feature")
assert result is False # Default value
def test_get_connection_feature_with_custom_default(self):
"""Test getting feature with custom default value."""
sockets_metadata = {}
result = get_connection_feature(
sockets_metadata, "missing_sid", "some_feature", default="custom_default"
)
assert result == "custom_default"
def test_get_connection_feature_with_feature_flags(self):
"""Test getting feature from connection with feature flags."""
sockets_metadata = {
"sid1": {
"feature_flags": {
"supports_preview_metadata": True,
"custom_feature": "value",
},
}
}
result = get_connection_feature(sockets_metadata, "sid1", "supports_preview_metadata")
assert result is True
result = get_connection_feature(sockets_metadata, "sid1", "custom_feature")
assert result == "value"
def test_get_connection_feature_missing_feature(self):
"""Test getting non-existent feature from connection."""
sockets_metadata = {
"sid1": {"feature_flags": {"existing_feature": True}}
}
result = get_connection_feature(sockets_metadata, "sid1", "missing_feature")
assert result is False
def test_supports_feature_returns_boolean(self):
"""Test that supports_feature always returns boolean."""
sockets_metadata = {
"sid1": {
"feature_flags": {
"bool_feature": True,
"string_feature": "value",
"none_feature": None,
},
}
}
# True boolean feature
assert supports_feature(sockets_metadata, "sid1", "bool_feature") is True
# Non-boolean values should return False
assert supports_feature(sockets_metadata, "sid1", "string_feature") is False
assert supports_feature(sockets_metadata, "sid1", "none_feature") is False
assert supports_feature(sockets_metadata, "sid1", "missing_feature") is False
def test_supports_feature_with_missing_connection(self):
"""Test supports_feature with missing connection."""
sockets_metadata = {}
assert supports_feature(sockets_metadata, "missing_sid", "any_feature") is False
def test_empty_feature_flags_dict(self):
"""Test connection with empty feature flags dictionary."""
sockets_metadata = {"sid1": {"feature_flags": {}}}
result = get_connection_feature(sockets_metadata, "sid1", "any_feature")
assert result is False
assert supports_feature(sockets_metadata, "sid1", "any_feature") is False
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