Hi, I was testing your lora which are great ^^, and I had a problem with something.
When testing your LoRa they work very well for me. hey try with the ones you have in the characters\BA folder, when trying with them it gave me this problem
"LoRA weight: 1, model: char-hina(e3b0c442) dimension: None, alpha: None, multiplier: 1 The selected model is not LoRA or not trained by sd-scripts? create LoRA for Text Encoder: 72 modules. create LoRA for U-Net: 192 modules. Error running process: D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\additional_networks.py Traceback (most recent call last): File "D:\011\stable-diffusion-webui\modules\scripts.py", line 357, in process script.process(p, *script_args) File "D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\additional_networks.py", line 238, in process network, info = lora_compvis.create_network_and_apply_compvis(du_state_dict, weight, text_encoder, unet) File "D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\lora_compvis.py", line 102, in create_network_and_apply_compvis state_dict = network.apply_lora_modules(du_state_dict) # some weights are applied to text encoder File "D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\lora_compvis.py", line 288, in apply_lora_modules state_dict = LoRANetworkCompvis.convert_state_dict_name_to_compvis(self.v2, du_state_dict) File "D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\lora_compvis.py", line 193, in convert_state_dict_name_to_compvis compvis_name = LoRANetworkCompvis.convert_diffusers_name_to_compvis(v2, tokens[0]) File "D:\011\stable-diffusion-webui\extensions\sd-webui-additional-networks\scripts\lora_compvis.py", line 182, in convert_diffusers_name_to_compvis assert cv_name is not None, f"conversion failed: {du_name}" AssertionError: conversion failed: string_to_token", any solution?
Your LoRa work is amazing. Thank you.
I almost never come to the site page for uploading so I never checked inbox so sorry for the late reply,
you are using textual inversion embeddings as Lora, everything in the Lora folders are Loras and rest are TI embeddings