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a495b1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | """Pre-compute Vera material identity embeddings for zero-token identity injection."""
import torch, os
os.environ["TOKENIZERS_PARALLELISM"] = "false"
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.to("mps")
pipe.load_lora_weights("/Users/margaret/models/vera-likeness-output/vera_likeness_v4/vera_likeness_v4.safetensors", adapter_name="likeness")
pipe.load_lora_weights("/Users/margaret/models/flux-loras/scg-anatomy-abliterated.safetensors", adapter_name="anatomy")
pipe.load_lora_weights("/Users/margaret/models/kintsugi-texture-output/kintsugi_texture_v1/kintsugi_texture_v1.safetensors", adapter_name="kintsugi")
pipe.set_adapters(["likeness", "anatomy", "kintsugi"], adapter_weights=[1.0, 0.7, 1.0])
print("Pipeline loaded with LoRAs")
identity_prompt = (
"vera with luminous amber gemstone eyes, dark navy matte ceramic figure, "
"NOT human skin, NOT glossy. Shattered and reassembled with abundant "
"gold-filled kintsugi cracks across cheekbones, down the neck, branching "
"across collarbones, ribs, hips, spine, and thighs. Thick gold repair "
"lines with visible depth following natural fracture patterns. The gold "
"glows from within. Matte blue-black fired ceramic surface texture."
)
print("Encoding identity embeddings...")
identity_embeds = pipe.encode_prompt(
prompt=identity_prompt,
prompt_2=identity_prompt,
max_sequence_length=512,
)
out_dir = "/Users/margaret/models/vera-triple-stack/identity_cache"
os.makedirs(out_dir, exist_ok=True)
for i, emb in enumerate(identity_embeds):
if emb is not None:
path = os.path.join(out_dir, f"identity_embed_{i}.pt")
torch.save(emb.cpu(), path)
print(f"Saved embed {i}: shape={emb.shape}, path={path}")
else:
print(f"Embed {i}: None")
print("\nIdentity embeddings cached.")
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