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
- Atomic Chat new
- 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 comfy.model_management | |
| import comfy.memory_management | |
| import comfy_aimdo.host_buffer | |
| import comfy_aimdo.torch | |
| import psutil | |
| from comfy.cli_args import args | |
| def get_pin(module): | |
| return getattr(module, "_pin", None) | |
| def pin_memory(module): | |
| if module.pin_failed or args.disable_pinned_memory or get_pin(module) is not None: | |
| return | |
| #FIXME: This is a RAM cache trigger event | |
| ram_headroom = comfy.memory_management.RAM_CACHE_HEADROOM | |
| #we split the difference and assume half the RAM cache headroom is for us | |
| if ram_headroom > 0 and psutil.virtual_memory().available < (ram_headroom * 0.5): | |
| comfy.memory_management.extra_ram_release(ram_headroom) | |
| size = comfy.memory_management.vram_aligned_size([ module.weight, module.bias ]) | |
| if comfy.model_management.MAX_PINNED_MEMORY <= 0 or (comfy.model_management.TOTAL_PINNED_MEMORY + size) > comfy.model_management.MAX_PINNED_MEMORY: | |
| module.pin_failed = True | |
| return False | |
| try: | |
| hostbuf = comfy_aimdo.host_buffer.HostBuffer(size) | |
| except RuntimeError: | |
| module.pin_failed = True | |
| return False | |
| module._pin = comfy_aimdo.torch.hostbuf_to_tensor(hostbuf) | |
| module._pin_hostbuf = hostbuf | |
| comfy.model_management.TOTAL_PINNED_MEMORY += size | |
| return True | |
| def unpin_memory(module): | |
| if get_pin(module) is None: | |
| return 0 | |
| size = module._pin.numel() * module._pin.element_size() | |
| comfy.model_management.TOTAL_PINNED_MEMORY -= size | |
| if comfy.model_management.TOTAL_PINNED_MEMORY < 0: | |
| comfy.model_management.TOTAL_PINNED_MEMORY = 0 | |
| del module._pin | |
| del module._pin_hostbuf | |
| return size | |