d the embeddings with load_textual_inversion(), but this time, you’ll need two more parameters: weight_name: specifies the weight file to load if the file was saved in the 🤗 Diffusers format with a specific name or if the file is stored in the A1111 format token: specifies the special word to use in the prompt to trigger the embeddings Let’s load the sayakpaul/EasyNegative-test embeddings:   Copied pipeline.load_textual_inversion(
    "sayakpau