easygoing0114

/

flan-t5-xxl-fused

like 5

StateDict Keys: {'transformer': 776, 'vae': 244, 'text_encoder': 196, 'text_encoder_2': 221, 'ignore': 0}
Using Detected T5 Data Type: gguf
Using pre-quant state dict!
GGUF state dict: {'Q6_K': 169, 'Q8_0': 1}
Traceback (most recent call last):
File "D:\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 30, in work
self.result = self.func(*self.args, **self.kwargs)
File "D:\stable-diffusion-webui-forge\modules\txt2img.py", line 131, in txt2img_function
processed = processing.process_images(p)
File "D:\stable-diffusion-webui-forge\modules\processing.py", line 836, in process_images
manage_model_and_prompt_cache(p)
File "D:\stable-diffusion-webui-forge\modules\processing.py", line 804, in manage_model_and_prompt_cache
p.sd_model, just_reloaded = forge_model_reload()
File "D:\stable-diffusion-webui-forge\venv\lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "D:\stable-diffusion-webui-forge\modules\sd_models.py", line 504, in forge_model_reload
sd_model = forge_loader(state_dict, additional_state_dicts=additional_state_dicts)
File "D:\stable-diffusion-webui-forge\venv\lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "D:\stable-diffusion-webui-forge\backend\loader.py", line 520, in forge_loader
component = load_huggingface_component(estimated_config, component_name, lib_name, cls_name, local_path, component_sd)
File "D:\stable-diffusion-webui-forge\backend\loader.py", line 109, in load_huggingface_component
load_state_dict(model, state_dict, log_name=cls_name, ignore_errors=['transformer.encoder.embed_tokens.weight', 'logit_scale'])
File "D:\stable-diffusion-webui-forge\backend\state_dict.py", line 5, in load_state_dict
missing, unexpected = model.load_state_dict(sd, strict=False)
File "D:\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 2581, in load_state_dict
raise RuntimeError(
RuntimeError: Error(s) in loading state_dict for IntegratedT5:
While copying the parameter named "transformer.encoder.block.0.layer.0.SelfAttention.relative_attention_bias.weight", whose dimensions in the model are torch.Size([32, 64]) and whose dimensions in the checkpoint are torch.Size([32, 68]), an exception occurred : ('The size of tensor a (64) must match the size of tensor b (68) at non-singleton dimension 1',).
While copying the parameter named "transformer.shared.weight", whose dimensions in the model are torch.Size([32128, 4096]) and whose dimensions in the checkpoint are torch.Size([32128, 3360]), an exception occurred : ('The size of tensor a (4096) must match the size of tensor b (3360) at non-singleton dimension 1',).
Error(s) in loading state_dict for IntegratedT5:
While copying the parameter named "transformer.encoder.block.0.layer.0.SelfAttention.relative_attention_bias.weight", whose dimensions in the model are torch.Size([32, 64]) and whose dimensions in the checkpoint are torch.Size([32, 68]), an exception occurred : ('The size of tensor a (64) must match the size of tensor b (68) at non-singleton dimension 1',).
While copying the parameter named "transformer.shared.weight", whose dimensions in the model are torch.Size([32128, 4096]) and whose dimensions in the checkpoint are torch.Size([32128, 3360]), an exception occurred : ('The size of tensor a (4096) must match the size of tensor b (3360) at non-singleton dimension 1',).