import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("DFloat11/FLUX.1-Kontext-dev-DF11", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("marc8460/sienna-blaze-lora-v1")
prompt = "ASCII\u0000\u0000\u0000Image generated by Pykaso.ai"
image = pipe(prompt).images[0]Sienna Blaze – LoRA v1 for FLUX.1
- Prompt
- ASCIIImage generated by Pykaso.ai
Model description
This LoRA was trained on 13 image pairs of Sienna Blaze using Flux Kontext Trainer. It's designed for use with FLUX.1 Kontext-dev. Ideal for photorealistic influencer-style generations.
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Model tree for marc8460/sienna-blaze-lora-v1
Base model
black-forest-labs/FLUX.1-Kontext-dev Quantized
DFloat11/FLUX.1-Kontext-dev-DF11