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use original unet for HF models, don't download TE

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Kohya S
2023-06-14 22:26:05 +09:00
parent 44404fcd6d
commit 449ad7502c
3 changed files with 52 additions and 11 deletions
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29
library/model_util.py
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@@ -933,10 +933,31 @@ def load_models_from_stable_diffusion_checkpoint(v2, ckpt_path, device="cpu", dt
else:
converted_text_encoder_checkpoint = convert_ldm_clip_checkpoint_v1(state_dict)
logging.set_verbosity_error() # don't show annoying warning
text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14").to(device)
logging.set_verbosity_warning()
# logging.set_verbosity_error() # don't show annoying warning
# text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14").to(device)
# logging.set_verbosity_warning()
# print(f"config: {text_model.config}")
cfg = CLIPTextConfig(
vocab_size=49408,
hidden_size=768,
intermediate_size=3072,
num_hidden_layers=12,
num_attention_heads=12,
max_position_embeddings=77,
hidden_act="quick_gelu",
layer_norm_eps=1e-05,
dropout=0.0,
attention_dropout=0.0,
initializer_range=0.02,
initializer_factor=1.0,
pad_token_id=1,
bos_token_id=0,
eos_token_id=2,
model_type="clip_text_model",
projection_dim=768,
torch_dtype="float32",
)
text_model = CLIPTextModel._from_config(cfg)
info = text_model.load_state_dict(converted_text_encoder_checkpoint)
print("loading text encoder:", info)