flux_lora_natalie-diffusion

10
1 language
—
by
ZennyKenny
Image Model
OTHER
New
10 downloads
Early-stage
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Quick Summary

This is a LoRA for the FLUX.

Code Examples

Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Trigger wordspython
import replicate

input = {
    "prompt": "XTON",
    "lora_weights": "https://huggingface.co/ZennyKenny/flux_lora_natalie-diffusion/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]
Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('ZennyKenny/flux_lora_natalie-diffusion', weight_name='lora.safetensors')
image = pipeline('XTON').images[0]

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