Views
No views yet
to trigger concept `hsfw` → use `<s0><s1><s2><s3><s4><s5><s6><s7><s8><s9><s10><s11><s12><s13><s14><s15><s16><s17><s18><s19><s20><s21><s22><s23><s24><s25><s26><s27><s28><s29><s30><s31><s32><s33><s34><s35><s36><s37><s38>` in your prompt
1from diffusers import AutoPipelineForText2Image
2import torch
3from huggingface_hub import hf_hub_download
4 from safetensors.torch import load_file
5
6pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
7pipeline.load_lora_weights('cwhuh/babyface_flux_dlora_hsfw_African_American', weight_name='pytorch_lora_weights.safetensors')
8embedding_path = hf_hub_download(repo_id='cwhuh/babyface_flux_dlora_hsfw_African_American', filename='/nas/checkpoints/sangmin/babyface_flux_dlora_hsfw_African_American_emb.safetensors', repo_type="model")
9 state_dict = load_file(embedding_path)
10 pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>", "<s2>", "<s3>", "<s4>", "<s5>", "<s6>", "<s7>", "<s8>", "<s9>", "<s10>", "<s11>", "<s12>", "<s13>", "<s14>", "<s15>", "<s16>", "<s17>", "<s18>", "<s19>", "<s20>", "<s21>", "<s22>", "<s23>", "<s24>", "<s25>", "<s26>", "<s27>", "<s28>", "<s29>", "<s30>", "<s31>", "<s32>", "<s33>", "<s34>", "<s35>", "<s36>", "<s37>", "<s38>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
11
12image = pipeline('A newborn <s0><s1><s2><s3><s4><s5><s6><s7><s8><s9><s10><s11><s12><s13><s14><s15><s16><s17><s18><s19><s20><s21><s22><s23><s24><s25><s26><s27><s28><s29><s30><s31><s32><s33><s34><s35><s36><s37><s38> baby. The baby is wearing a white beanie and is swaddled in a white blanket. The background is a soft, neutral white, matching the original clean studio aesthetic.').images[0]# TODO: add an example code snippet for running this diffusion pipeline