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save text_encoder_2 config, not whole model
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@ -32,6 +32,7 @@ from omegaconf import OmegaConf
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from tqdm import tqdm
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from transformers import (
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CLIPTextModel,
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CLIPTextConfig,
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CLIPTokenizer,
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AutoFeatureExtractor,
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BertTokenizerFast,
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@ -205,13 +206,15 @@ def download_conversion_models():
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pipeline = CLIPTextModel.from_pretrained(repo_id, subfolder="text_encoder", **kwargs)
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pipeline.save_pretrained(target_dir / 'stable-diffusion-2-clip' / 'text_encoder', safe_serialization=True)
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# sd-xl - tokenizer_2
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repo_id = "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k"
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_, model_name = repo_id.split('/')
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tokenizer_2 = CLIPTokenizer.from_pretrained(repo_id, **kwargs)
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tokenizer_2.save_pretrained(target_dir / model_name, safe_serialization=True)
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# for some reason config.json never downloads
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hf_download_with_resume(repo_id, target_dir / model_name, "config.json")
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pipeline = CLIPTokenizer.from_pretrained(repo_id, **kwargs)
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pipeline.save_pretrained(target_dir / model_name, safe_serialization=True)
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pipeline = CLIPTextConfig.from_pretrained(repo_id, **kwargs)
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pipeline.save_pretrained(target_dir / model_name, safe_serialization=True)
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# VAE
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logger.info('Downloading stable diffusion VAE')
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vae = AutoencoderKL.from_pretrained('stabilityai/sd-vae-ft-mse', **kwargs)
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@ -1711,7 +1711,7 @@ def convert_ckpt_to_diffusers(
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pipe.save_pretrained(
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dump_path,
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safe_serialization=is_safetensors_available(),
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safe_serialization=is_safetensors_available() and not no_safetensors,
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)
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def convert_controlnet_to_diffusers(
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