Formular for requests.
I am using AbyssOrangeMix3 (AOM3)
A weight at around ~0.7 is recommended, but other weights may also work in certain situations. Just play around with it and use what feels right to you.
The main prompt is "Lamy"
You can try the following combinations for her outfits:
If you don't want her to wear her hat, add "berret, hat" to negative prompts.
Base:
Lamy, Lamyoutfit
Second Outfit (Casual):
Lamy, LamyCasual, two side up
Third Outfit (Sleepwear):
Lamy, LamySleepwear, messy hair
Fourth Outfit (New Year's):
Lamy, LamyKimono, pink haori
Only add pink haori, if you want her to wear it.
I have not encountered any major problems with any of the outfits.
Please let me know if you have any issues.
Used embeddings for sample pictures:
If you have any feedback/requests/etc. just write in the comments or hit me up on reddit.
Description
FAQ
Comments (6)
网站资源出问题了，建议作者更新一下mod
There is something wrong with the website resources
Please check the model file
When do you get this error? I can download the file just fine.
deepl translation:
你什么时候得到这个错误？我可以正常下载文件。
Error completing request Arguments: ('task(we82bs5wj6hnmz7)', 'Masterpiece, <lora:yukihanaLamyHololive_v10:1>, 1girl, Lamy', '(EasyNegative:0.9),', [], 30, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 768, 576, False, 0.7, 2, 'Latent', 0, 0, 0, [], 0, False, 'MultiDiffusion', False, 10, 1, 1, 64, False, True, 1024, 1024, 96, 96, 48, 1, 'None', 2, False, False, False, False, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, False, True, True, False, 1536, 96, False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, None, 'Refresh models', False, 'none', 'None', 1, None, False, 'Scale to Fit (Inner Fit)', False, False, 64, 64, 64, 1, False, 0.9, 5, '0.0001', False, 'None', '', 0.1, False, False, False, 'positive', 'comma', 0, False, False, '', 1, '', 0, '', 0, '', True, False, False, False, 0) {} Traceback (most recent call last): File "E:\Git\stable-diffusion-webui\modules\call_queue.py", line 56, in f res = list(func(*args, **kwargs)) File "E:\Git\stable-diffusion-webui\modules\call_queue.py", line 37, in f res = func(*args, **kwargs) File "E:\Git\stable-diffusion-webui\modules\txt2img.py", line 56, in txt2img processed = process_images(p) File "E:\Git\stable-diffusion-webui\modules\processing.py", line 486, in process_images res = process_images_inner(p) File "E:\Git\stable-diffusion-webui\modules\processing.py", line 625, in process_images_inner uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps, cached_uc) File "E:\Git\stable-diffusion-webui\modules\processing.py", line 570, in get_conds_with_caching cache[1] = function(shared.sd_model, required_prompts, steps) File "E:\Git\stable-diffusion-webui\modules\prompt_parser.py", line 140, in get_learned_conditioning conds = model.get_learned_conditioning(texts) File "E:\Git\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 669, in get_learned_conditioning c = self.cond_stage_model(c) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\modules\sd_hijack_clip.py", line 229, in forward z = self.process_tokens(tokens, multipliers) File "E:\Git\stable-diffusion-webui\extensions\stable-diffusion-webui-aesthetic-gradients\aesthetic_clip.py", line 202, in __call__ z = self.process_tokens(remade_batch_tokens, multipliers) File "E:\Git\stable-diffusion-webui\modules\sd_hijack_clip.py", line 254, in process_tokens z = self.encode_with_transformers(tokens) File "E:\Git\stable-diffusion-webui\modules\sd_hijack_clip.py", line 302, in encode_with_transformers outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\transformers\models\clip\modeling_clip.py", line 811, in forward return self.text_model( File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\transformers\models\clip\modeling_clip.py", line 721, in forward encoder_outputs = self.encoder( File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\transformers\models\clip\modeling_clip.py", line 650, in forward layer_outputs = encoder_layer( File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\transformers\models\clip\modeling_clip.py", line 379, in forward hidden_states, attn_weights = self.self_attn( File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\transformers\models\clip\modeling_clip.py", line 268, in forward query_states = self.q_proj(hidden_states) * self.scale File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\extensions-builtin\Lora\lora.py", line 197, in lora_Linear_forward return lora_forward(self, input, torch.nn.Linear_forward_before_lora(self, input)) File "E:\Git\stable-diffusion-webui\extensions\a1111-sd-webui-locon\scripts\main.py", line 494, in lora_forward res = res + module.inference(x) * scale File "E:\Git\stable-diffusion-webui\extensions\a1111-sd-webui-locon\scripts\main.py", line 219, in inference return self.up_model(self.down_model(x)) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\Git\stable-diffusion-webui\extensions-builtin\Lora\lora.py", line 197, in lora_Linear_forward return lora_forward(self, input, torch.nn.Linear_forward_before_lora(self, input)) File "E:\Git\stable-diffusion-webui\py310\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward return F.linear(input, self.weight, self.bias) RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument mat2 in method wrapper_CUDA_mm)
i dunno what cause this but when using this version lamy lora will got this. the one and only tho. probably its my problem idk XD
@Mythy Mh... I'm still doing some testing myself and I asked people on my discord to try redownloading this LoRA and using it. So far it worked for everyone :/
What really puzzles me is that you are only having this problem with this specific LoRA and I can't really think of anything that would result in this. Especially since you can use my Kronii LoRA without a problem.
I'm gonna see if I can find someone else for whom my LoRA breaks to see if it's a general problem on my side. If not I don't think I can do much for you :( Maybe try using it with an up to date version of the additional networks extension?
@ChameleonAI im not using addnet lol. just write lora in prompt tho
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