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to trigger concept `TOK` → use `<s0><s1>` 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('linoyts/huggy_flux_1500_ti_1_rank_16_embeds', weight_name='pytorch_lora_weights.safetensors')
8embedding_path = hf_hub_download(repo_id='linoyts/huggy_flux_1500_ti_1_rank_16_embeds', filename='huggy_flux_1500_ti_1_rank_16_embeds_emb.safetensors', repo_type="model")
9 state_dict = load_file(embedding_path)
10 pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
11
12image = pipeline('a <s0><s1> hugging face emoji').images[0]# TODO: add an example code snippet for running this diffusion pipeline