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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Model tree for davidrd123/Flux-RangeRover-AIToolkit
Base model
black-forest-labs/FLUX.1-dev