loraSayed
Model trained with AI Toolkit by Ostris

- Prompt
- [trigger] ADscenario describing a left turn intersection. The ego vehicle wants to turn left

- Prompt
- [trigger] ADscenario describing a driving maneuver on highway. The ego vehicle drives behind a front vehicle on the right lane on the highway

- Prompt
- [trigger] ADscenario describing a an evasion maneuver. The ego vehicle change the lane in urban environment

- Prompt
- [trigger] ADscenario describing a driving situation in a construction site. The ego vehicle drives between cones

- Prompt
- [trigger] ADscenario describing a traffic light driving situation. The ego vehicle stops for a red light
Trigger words
You should use ADscenario
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-schnell', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('TFree2035/FluxScenario2', weight_name='loraSayed.safetensors')
image = pipeline('[trigger] ADscenario describing a left turn intersection. The ego vehicle wants to turn left').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 Free2035/FluxScenario2
Base model
black-forest-labs/FLUX.1-schnell