mirror of https://github.com/vladmandic/automatic
39 lines
1.5 KiB
Python
39 lines
1.5 KiB
Python
import transformers
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import diffusers
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from huggingface_hub import file_exists
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from modules import shared, devices, sd_models, model_quant, sd_hijack_te
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from pipelines import generic
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def load_pixart(checkpoint_info, diffusers_load_config={}):
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repo_id = sd_models.path_to_repo(checkpoint_info)
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sd_models.hf_auth_check(checkpoint_info)
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repo_id_tenc = repo_id
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repo_id_pipe = repo_id
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if not file_exists(repo_id_tenc, "text_encoder/config.json"):
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repo_id_tenc = "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS"
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if not file_exists(repo_id_pipe, "model_index.json"):
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repo_id_pipe = "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS"
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load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
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shared.log.debug(f'Load model: type=AuraFlow repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
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transformer = generic.load_transformer(repo_id, cls_name=diffusers.PixArtTransformer2DModel, load_config=diffusers_load_config)
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text_encoder = generic.load_text_encoder(repo_id_tenc, cls_name=transformers.T5EncoderModel, load_config=diffusers_load_config)
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pipe = diffusers.PixArtSigmaPipeline.from_pretrained(
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repo_id_pipe,
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transformer=transformer,
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text_encoder=text_encoder,
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cache_dir=shared.opts.diffusers_dir,
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**load_args,
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)
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del text_encoder
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del transformer
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sd_hijack_te.init_hijack(pipe)
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devices.torch_gc(force=True, reason='load')
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return pipe
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