furry-enhancer

132

2

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by

Keltezaa

Image Model

OTHER

New

132 downloads

Early-stage

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Quick Summary

AI model with specialized capabilities.

Code Examples

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)pythonpytorch

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/furry-enhancer', weight_name='Furry_Enhancer PhotoV3.420.safetensors')
image = pipeline('`Anthro`, `Furry`, `Photo`').images[0]

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