Flux Dev Anne Hathaway Lora

114
2
1 language
license:apache-2.0
by
flymy-ai
Image Model
OTHER
New
114 downloads
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Quick Summary

Agentic Infra for GenAI.

Code Examples

🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)
🧪 Usagepythonpytorch
from diffusers import DiffusionPipeline
import torch

model_name = "black-forest-labs/FLUX.1-dev"

# Load the pipeline
if torch.cuda.is_available():
    torch_dtype = torch.bfloat16
    device = "cuda"
else:
    torch_dtype = torch.float32
    device = "cpu"

pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)

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