Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

Ltx-3

File size: 789 Bytes

e00eceb

#easyuse_groups_map{
  flex-direction: column;
  align-items: end;
  display:flex;position: absolute;
  top: 50px; left: 10px; width: 180px;
  border-radius:12px;
  min-height:100px;
  max-height:400px;
  color: var(--descrip-text);
  background-color: var(--comfy-menu-bg);
  padding: 10px 4px;
  border: 1px solid var(--border-color);
  z-index: 399;
  padding-top: 0;
}
#easyuse_groups_map .icon{
  width: 12px;
  height:12px;
}
#easyuse_groups_map .closeBtn{
  float: right;
  color: var(--input-text);
  border-radius:30px;
  background-color: var(--comfy-input-bg);
  border: 1px solid var(--border-color);
  cursor: pointer;
  aspect-ratio: 1 / 1;
  display: flex;
  justify-content: center;
  align-items: center;
}
#easyuse_groups_map .closeBtn:hover{
  filter:brightness(120%);
}