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: 18,194 Bytes
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from .imagefunc import AnyType, log, extract_all_numbers_from_str
any = AnyType("*")
class SeedNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"seed":("INT", {"default": 0, "min": 0, "max": 1e18, "step": 1}),
},}
RETURN_TYPES = ("INT",)
RETURN_NAMES = ("seed",)
FUNCTION = 'seed_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def seed_node(self, seed):
return (seed,)
class BooleanOperator:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
operator_list = ["==", "!=", ">", "<", ">=", "<=", "and", "or", "xor", "not(a)", "min", "max"]
return {"required": {
"a": (any, ),
"b": (any, ),
"operator": (operator_list,),
},}
RETURN_TYPES = ("BOOLEAN",)
RETURN_NAMES = ("output",)
FUNCTION = 'bool_operator_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def bool_operator_node(self, a, b, operator):
ret_value = False
if operator == "==":
ret_value = a == b
if operator == "!=":
ret_value = a != b
if operator == ">":
ret_value = a > b
if operator == "<":
ret_value = a < b
if operator == ">=":
ret_value = a >= b
if operator == "<=":
ret_value = a <= b
if operator == "and":
ret_value = a and b
if operator == "or":
ret_value = a or b
if operator == "xor":
ret_value = not(a == b)
if operator == "not(a)":
ret_value = not a
if operator == "min":
ret_value = min(a, b)
if operator == "max":
ret_value = max(a, b)
return (ret_value,)
class BooleanOperatorV2:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
operator_list = ["==", "!=", ">", "<", ">=", "<=", "and", "or", "xor", "not(a)", "min", "max"]
return {
"required":
{
"a_value": ("STRING", {"default": "", "multiline": False}),
"b_value": ("STRING", {"default": "", "multiline": False}),
"operator": (operator_list,),
},
"optional": {
"a": (any,),
"b": (any,),
}
}
RETURN_TYPES = ("BOOLEAN", "STRING",)
RETURN_NAMES = ("output", "string",)
FUNCTION = 'bool_operator_node_v2'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def bool_operator_node_v2(self, a_value, b_value, operator, a = None, b = None):
if a is None:
if a_value != "":
_numbers = extract_all_numbers_from_str(a_value, checkint=True)
if len(_numbers) > 0:
a = _numbers[0]
else:
a = 0
else:
a = 0
if b is None:
if b_value != "":
_numbers = extract_all_numbers_from_str(b_value, checkint=True)
if len(_numbers) > 0:
b = _numbers[0]
else:
b = 0
else:
b = 0
ret_value = False
if operator == "==":
ret_value = a == b
if operator == "!=":
ret_value = a != b
if operator == ">":
ret_value = a > b
if operator == "<":
ret_value = a < b
if operator == ">=":
ret_value = a >= b
if operator == "<=":
ret_value = a <= b
if operator == "and":
ret_value = a and b
if operator == "or":
ret_value = a or b
if operator == "xor":
ret_value = not(a == b)
if operator == "not(a)":
ret_value = not a
if operator == "min":
ret_value = min(a, b)
if operator == "max":
ret_value = max(a, b)
return (ret_value, str(ret_value))
class NumberCalculator:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
operator_list = ["+", "-", "*", "/", "**", "//", "%", "nth_root", "min", "max"]
return {"required": {
"a": (any, {}),
"b": (any, {}),
"operator": (operator_list,),
},}
RETURN_TYPES = ("INT", "FLOAT",)
RETURN_NAMES = ("int", "float",)
FUNCTION = 'number_calculator_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def number_calculator_node(self, a, b, operator):
ret_value = 0
if operator == "+":
ret_value = a + b
if operator == "-":
ret_value = a - b
if operator == "*":
ret_value = a * b
if operator == "**":
ret_value = a ** b
if operator == "%":
ret_value = a % b
if operator == "nth_root":
ret_value = a ** (1/b)
if operator == "min":
ret_value = min(a, b)
if operator == "max":
ret_value = max(a, b)
if operator == "/":
if b != 0:
ret_value = a / b
else:
ret_value = 0
if operator == "//":
if b != 0:
ret_value = a // b
else:
ret_value = 0
return (int(ret_value), float(ret_value),)
class NumberCalculatorV2:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
operator_list = ["+", "-", "*", "/", "**", "//", "%" , "nth_root", "min", "max"]
return {
"required":
{
"a_value": ("STRING", {"default": "", "multiline": False}),
"b_value": ("STRING", {"default": "", "multiline": False}),
"operator": (operator_list,),
},
"optional": {
"a": (any,),
"b": (any,),
}
}
RETURN_TYPES = ("INT", "FLOAT", "STRING",)
RETURN_NAMES = ("int", "float", "string",)
FUNCTION = 'number_calculator_node_v2'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def number_calculator_node_v2(self, a_value, b_value, operator, a = None, b = None):
if a is None:
if a_value != "":
_numbers = extract_all_numbers_from_str(a_value, checkint=True)
if len(_numbers) > 0:
a = _numbers[0]
else:
a = 0
else:
a = 0
if b is None:
if b_value != "":
_numbers = extract_all_numbers_from_str(b_value, checkint=True)
if len(_numbers) > 0:
b = _numbers[0]
else:
b = 0
else:
b = 0
ret_value = 0
if operator == "+":
ret_value = a + b
if operator == "-":
ret_value = a - b
if operator == "*":
ret_value = a * b
if operator == "**":
ret_value = a ** b
if operator == "%":
ret_value = a % b
if operator == "nth_root":
ret_value = a ** (1/b)
if operator == "min":
ret_value = min(a, b)
if operator == "max":
ret_value = max(a, b)
if operator == "/":
if b != 0:
ret_value = a / b
else:
ret_value = 0
if operator == "//":
if b != 0:
ret_value = a // b
else:
ret_value = 0
return (int(ret_value), float(ret_value), str(ret_value))
class StringCondition:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
string_condition_list = ["include", "exclude", "equal"]
return {"required": {
"text": ("STRING", {"multiline": False}),
"condition": (string_condition_list,),
"sub_string": ("STRING", {"multiline": False}),
},}
RETURN_TYPES = ("BOOLEAN", "STRING",)
RETURN_NAMES = ("output", "string",)
FUNCTION = 'string_condition'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def string_condition(self, text, condition, sub_string):
ret = False
if condition == "include":
ret = sub_string in text
if condition == "exclude":
ret = sub_string not in text
if condition == "equal":
ret = text == sub_string
return (ret, str(ret))
class TextBoxNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"text": ("STRING", {"multiline": True}),
},}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("text",)
FUNCTION = 'text_box_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def text_box_node(self, text):
return (text,)
class StringNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"string": ("STRING", {"multiline": False}),
},}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("string",)
FUNCTION = 'string_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def string_node(self, string):
return (string,)
class IntegerNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"int_value":("INT", {"default": 0, "min": -1e18, "max": 1e18, "step": 1}),
},}
RETURN_TYPES = ("INT", "STRING",)
RETURN_NAMES = ("int", "string",)
FUNCTION = 'integer_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def integer_node(self, int_value):
return (int(int_value), str(int_value))
class FloatNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"float_value": ("FLOAT", {"default": 0, "min": -1e18, "max": 1e18, "step": 0.00001}),
},}
RETURN_TYPES = ("FLOAT", "STRING",)
RETURN_NAMES = ("float", "string",)
FUNCTION = 'float_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def float_node(self, float_value):
return (float_value, str(float_value))
class BooleanNode:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
return {"required": {
"bool_value": ("BOOLEAN", {"default": False}),
},}
RETURN_TYPES = ("BOOLEAN", "STRING",)
RETURN_NAMES = ("boolean", "string",)
FUNCTION = 'boolean_node'
CATEGORY = '😺dzNodes/LayerUtility/Data'
def boolean_node(self, bool_value):
return (bool_value, str(bool_value))
class IfExecute:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"if_condition": (any,),
"when_TRUE": (any,),
"when_FALSE": (any,),
},
}
RETURN_TYPES = (any,)
RETURN_NAMES = ("?",)
FUNCTION = "if_execute"
CATEGORY = '😺dzNodes/LayerUtility/Data'
def if_execute(self, if_condition, when_TRUE, when_FALSE):
return (when_TRUE if if_condition else when_FALSE,)
class SwitchCaseNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"switch_condition": ("STRING", {"default": "", "multiline": False}),
"case_1": ("STRING", {"default": "", "multiline": False}),
"case_2": ("STRING", {"default": "", "multiline": False}),
"case_3": ("STRING", {"default": "", "multiline": False}),
"input_default": (any,),
},
"optional": {
"input_1": (any,),
"input_2": (any,),
"input_3": (any,),
}
}
RETURN_TYPES = (any,)
RETURN_NAMES = ("?",)
FUNCTION = "switch_case"
CATEGORY = '😺dzNodes/LayerUtility/Data'
def switch_case(self, switch_condition, case_1, case_2, case_3, input_default, input_1=None, input_2=None, input_3=None):
output=input_default
if switch_condition == case_1 and input_1 is not None:
output=input_1
elif switch_condition == case_2 and input_2 is not None:
output=input_2
elif switch_condition == case_3 and input_3 is not None:
output=input_3
return (output,)
class QueueStopNode():
def __init__(self):
pass
@classmethod
def INPUT_TYPES(self):
mode_list = ["stop", "continue"]
return {
"required": {
"any": (any, ),
"mode": (mode_list,),
"stop": ("BOOLEAN", {"default": True}),
},
}
RETURN_TYPES = (any,)
RETURN_NAMES = ("any",)
FUNCTION = 'stop_node'
CATEGORY = '😺dzNodes/LayerUtility/SystemIO'
def stop_node(self, any, mode,stop):
if mode == "stop":
if stop:
log(f"Queue stopped, it was terminated by node.", "error")
from comfy.model_management import InterruptProcessingException
raise InterruptProcessingException()
return (any,)
class LS_ImageBatchToMultiList:
def __init__(self):
self.NODE_NAME = 'ImageBatchToList'
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
"batch_size": ("INT", {
"default": 6,
"min": 1,
"max": 64,
"step": 1
}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image", )
OUTPUT_IS_LIST = (True,)
FUNCTION = "image_batch_to_multi_list"
CATEGORY = '😺dzNodes/LayerUtility/Data'
def image_batch_to_multi_list(self, image, batch_size):
"""
image: [B, H, W, C]
输出: list of IMAGE batch,每个 batch 大小 <= batch_size
"""
B = image.shape[0]
out = []
sizes = []
for i in range(0, B, batch_size):
batch = image[i:i + batch_size]
out.append(batch)
sizes.append(batch.shape[0])
log(f"{self.NODE_NAME}: Convert a batch of {B} images to {sizes}.", message_type='finish')
return (out,)
class LS_MultiImageListToBatch:
def __init__(self):
self.NODE_NAME = 'ImageListToBatch'
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("image", )
INPUT_IS_LIST = True
FUNCTION = "multi_image_list_to_batch"
CATEGORY = '😺dzNodes/LayerUtility/Data'
def multi_image_list_to_batch(self, image):
"""
image: list of IMAGE batch
每个元素 shape 为 [Bi, Hi, Wi, C]
输出: 单一 IMAGE batch [sum(Bi), H, W, C]
"""
# 以第一个 batch 的第一张图作为基准尺寸
base_h, base_w = image[0].shape[1:3]
out = []
sizes = []
for batch in image:
# batch: [B, H, W, C]
if batch.shape[1:3] != (base_h, base_w):
# 转成 [B, C, H, W]
batch = batch.permute(0, 3, 1, 2)
batch = comfy.utils.common_upscale(
batch,
base_w,
base_h,
upscale_method="bicubic",
crop="center"
)
# 转回 [B, H, W, C]
batch = batch.permute(0, 2, 3, 1)
sizes.append(batch.shape[0])
out.append(batch)
# 沿 batch 维拼接
out = torch.cat(out, dim=0)
log(f"{self.NODE_NAME}: Convert {sizes} list(s) to a batch of {out.shape[0]} images.", message_type='finish')
return (out,)
NODE_CLASS_MAPPINGS = {
"LayerUtility: QueueStop": QueueStopNode,
"LayerUtility: SwitchCase": SwitchCaseNode,
"LayerUtility: If ": IfExecute,
"LayerUtility: StringCondition": StringCondition,
"LayerUtility: BooleanOperator": BooleanOperator,
"LayerUtility: NumberCalculator": NumberCalculator,
"LayerUtility: BooleanOperatorV2": BooleanOperatorV2,
"LayerUtility: NumberCalculatorV2": NumberCalculatorV2,
"LayerUtility: TextBox": TextBoxNode,
"LayerUtility: String": StringNode,
"LayerUtility: Integer": IntegerNode,
"LayerUtility: Float": FloatNode,
"LayerUtility: Boolean": BooleanNode,
"LayerUtility: Seed": SeedNode,
"LayerUtility: ImageBatchToList": LS_ImageBatchToMultiList,
"LayerUtility: ImageListToBatch": LS_MultiImageListToBatch,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LayerUtility: QueueStop": "LayerUtility: Queue Stop",
"LayerUtility: SwitchCase": "LayerUtility: Switch Case",
"LayerUtility: If ": "LayerUtility: If",
"LayerUtility: StringCondition": "LayerUtility: String Condition",
"LayerUtility: BooleanOperator": "LayerUtility: Boolean Operator",
"LayerUtility: NumberCalculator": "LayerUtility: Number Calculator",
"LayerUtility: BooleanOperatorV2": "LayerUtility: Boolean Operator V2",
"LayerUtility: NumberCalculatorV2": "LayerUtility: Number Calculator V2",
"LayerUtility: TextBox": "LayerUtility: TextBox",
"LayerUtility: String": "LayerUtility: String",
"LayerUtility: Integer": "LayerUtility: Integer",
"LayerUtility: Float": "LayerUtility: Float",
"LayerUtility: Boolean": "LayerUtility: Boolean",
"LayerUtility: Seed": "LayerUtility: Seed",
"LayerUtility: ImageBatchToList": "LayerUtility: Image Batch To List(Multi)",
"LayerUtility: ImageListToBatch": "LayerUtility: Image List To Batch(Multi)",
} |