restore_photo_v3.1-lora

9

—

by

cyburn

Image Model

OTHER

New

9 downloads

Early-stage

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Mobile

Laptop

Server

Quick Summary

Download model and use it with ComfyUI, AUTOMATIC1111, SD.

Code Examples

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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-Kontext-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('cyburn/restore_photo_v3.1-lora', weight_name='restore_photo_v3.1_000000250.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

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