Qwen-Image-HeadshotX
109
40
license:apache-2.0
by
prithivMLmods
Image Model
OTHER
New
109 downloads
Early-stage
Edge AI:
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Mobile
Laptop
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Quick Summary
> [!note] Qwen-Image-HeadshotX is a super-realistic headshot adapter for Qwen-Image, an image generation model by Qwen. It is an advanced LoRA adaptation of the...
Code Examples
Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Inference Rangepythonpytorch
import torch
from diffusers import DiffusionPipeline
base_model = "Qwen/Qwen-Image"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "prithivMLmods/Qwen-Image-HeadshotX"
trigger_word = "face headshot"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)Deploy This Model
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