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range_rover_ait_v2

Model trained with AI Toolkit by Ostris

Prompt
Medium shot, rear three-quarter angle of a c4r set against a white background
Prompt
Close-up, rear angle of a c4r set against a white background
Prompt
Closeup, frontal angle of a c4r set against a white background
Prompt
Three-quarter rear angle medium shot of a c4r set against a white background
Prompt
Profile view, medium shot of a c4r set against a white background
Prompt
A close-up, rearview shot of a c4r set against a white background
Prompt
Medium shot of a c4r parked at the edge of a volcanic crater with steam rising in the background
Prompt
Three-quarter front angle of a c4r stopping at a red light in Times Square at night
Prompt
Three-quarter rear view of a c4r kicking up dust on a desert trail at sunset
Prompt
Close-up of a c4r's wheel kicking up snow as it climbs a winding mountain road
Prompt
Wide shot of a c4r driving on a beach at sunset with surfers in the background

Trigger words

You should use c4r to trigger the image generation.

Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('davidrd123/Flux-RangeRover-AIToolkit', weight_name='range_rover_ait_v2.safetensors')
image = pipeline('Medium shot, rear three-quarter angle of a c4r set against a white background').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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