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---
license: cc
tags:
- text-to-image
- lora
- diffusers
- template:sd-lora
base_model:
- black-forest-labs/FLUX.1-dev
widget:
- text: brazil
output:
url: images/brazil.png
- text: canada, geoguessr
output:
url: images/canada.png
- text: mongolia
output:
url: images/mongolia.png
- text: serbia village
output:
url: images/serbia.png
- text: thailand
output:
url: images/thailand.png
---
# fake geoguessr locations lora for flux-dev
https://x.com/_lyraaaa_/status/1841762752404369745
rank 32, trained for 3500 steps on over 200 labeled locations. trigger word ("geoguessr") not always necessary, just name a location
**run this with diffusers:**
```py
import torch
from diffusers import FluxPipeline
import time
import random
# initialize pipeline and lora
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("cuda")
lora_weight = 0.8
pipe.load_lora_weights(
'/workspace/geoguessr_v1_000003500.safetensors',
adapter_name='geoguessr_v1'
)
pipe.set_adapters('geoguessr_v1', adapter_weights=[lora_weight])
# set params and generate
seed = -1
seed = seed if seed != -1 else random.randint(0, 2**32)
print(seed)
prompt = "sweden, snow"
out = pipe(
prompt=prompt,
guidance_scale=4,
height=624,
width=960,
num_inference_steps=40,
generator=torch.Generator("cuda").manual_seed(seed),
).images[0]
# save and display output
filename=f"{time.time()}.png"
out.save(filename)
from IPython.display import Image, display
display(Image(filename=filename))
```
**known model biases:**
- v1 of this model leans heavily towards rural locations due to dataset bias, will be fixed in v2 as i collect more data
- it managed to generalize to locations not available on geoguessr, like china, although it drifts towards generic locations
- its trained on lowercase country names, and flux is case sensitive. results may vary
- it LOVES orange/red dirt colors. this will be fixed in v2 also
geoguessr_v2 with a much larger dataset and less location bias will be out eventually.
since i do not own the data for this model, i can't really claim ownership of the model itself either. have fun!
<Gallery />
trained with https://github.com/ostris/ai-toolkit/blob/main/notebooks/FLUX_1_dev_LoRA_Training.ipynb
this model is a part of my much larger desterilizer project- a bit more here https://x.com/_lyraaaa_/status/1824003678086590646 |