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 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

Ltx-3 / ComfyUI /comfy_api_nodes /util /__init__.py

vidfom

Upload folder using huggingface_hub

e00eceb verified about 2 months ago

raw

history blame contribute delete

3.11 kB

	from ._helpers import get_fs_object_size
	from .client import (
	ApiEndpoint,
	poll_op,
	poll_op_raw,
	sync_op,
	sync_op_raw,
	)
	from .conversions import (
	audio_bytes_to_audio_input,
	audio_input_to_mp3,
	audio_ndarray_to_bytesio,
	audio_tensor_to_contiguous_ndarray,
	audio_to_base64_string,
	bytesio_to_image_tensor,
	convert_mask_to_image,
	downscale_image_tensor,
	downscale_image_tensor_by_max_side,
	image_tensor_pair_to_batch,
	pil_to_bytesio,
	resize_mask_to_image,
	tensor_to_base64_string,
	tensor_to_bytesio,
	tensor_to_pil,
	text_filepath_to_base64_string,
	text_filepath_to_data_uri,
	trim_video,
	video_to_base64_string,
	)
	from .download_helpers import (
	download_url_as_bytesio,
	download_url_to_bytesio,
	download_url_to_file_3d,
	download_url_to_image_tensor,
	download_url_to_video_output,
	)
	from .upload_helpers import (
	upload_3d_model_to_comfyapi,
	upload_audio_to_comfyapi,
	upload_file_to_comfyapi,
	upload_image_to_comfyapi,
	upload_images_to_comfyapi,
	upload_video_to_comfyapi,
	)
	from .validation_utils import (
	get_image_dimensions,
	get_number_of_images,
	validate_aspect_ratio_string,
	validate_audio_duration,
	validate_container_format_is_mp4,
	validate_image_aspect_ratio,
	validate_image_dimensions,
	validate_images_aspect_ratio_closeness,
	validate_string,
	validate_video_dimensions,
	validate_video_duration,
	validate_video_frame_count,
	)

	__all__ = [
	# API client
	"ApiEndpoint",
	"poll_op",
	"poll_op_raw",
	"sync_op",
	"sync_op_raw",
	# Upload helpers
	"upload_3d_model_to_comfyapi",
	"upload_audio_to_comfyapi",
	"upload_file_to_comfyapi",
	"upload_image_to_comfyapi",
	"upload_images_to_comfyapi",
	"upload_video_to_comfyapi",
	# Download helpers
	"download_url_as_bytesio",
	"download_url_to_bytesio",
	"download_url_to_file_3d",
	"download_url_to_image_tensor",
	"download_url_to_video_output",
	# Conversions
	"audio_bytes_to_audio_input",
	"audio_input_to_mp3",
	"audio_ndarray_to_bytesio",
	"audio_tensor_to_contiguous_ndarray",
	"audio_to_base64_string",
	"bytesio_to_image_tensor",
	"convert_mask_to_image",
	"downscale_image_tensor",
	"downscale_image_tensor_by_max_side",
	"image_tensor_pair_to_batch",
	"pil_to_bytesio",
	"resize_mask_to_image",
	"tensor_to_base64_string",
	"tensor_to_bytesio",
	"tensor_to_pil",
	"text_filepath_to_base64_string",
	"text_filepath_to_data_uri",
	"trim_video",
	"video_to_base64_string",
	# Validation utilities
	"get_image_dimensions",
	"get_number_of_images",
	"validate_aspect_ratio_string",
	"validate_audio_duration",
	"validate_container_format_is_mp4",
	"validate_image_aspect_ratio",
	"validate_image_dimensions",
	"validate_images_aspect_ratio_closeness",
	"validate_string",
	"validate_video_dimensions",
	"validate_video_duration",
	"validate_video_frame_count",
	# Misc functions
	"get_fs_object_size",
	]