mirror of https://github.com/vladmandic/automatic
43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
import os
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import gradio as gr
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from modules.shared import log, opts
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def hf_init():
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os.environ.setdefault('HF_HUB_DISABLE_EXPERIMENTAL_WARNING', '1')
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os.environ.setdefault('HF_HUB_DISABLE_SYMLINKS_WARNING', '1')
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os.environ.setdefault('HF_HUB_DISABLE_IMPLICIT_TOKEN', '1')
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os.environ.setdefault('HUGGINGFACE_HUB_VERBOSITY', 'warning')
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def hf_search(keyword):
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hf_init()
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import huggingface_hub as hf
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hf_api = hf.HfApi()
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models = hf_api.list_models(model_name=keyword, full=True, library="diffusers", limit=50, sort="downloads", direction=-1)
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data = []
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for model in models:
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tags = [t for t in model.tags if not t.startswith('diffusers') and not t.startswith('license') and not t.startswith('arxiv') and len(t) > 2]
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data.append([model.id, model.pipeline_tag, tags, model.downloads, model.lastModified, f'https://huggingface.co/{model.id}'])
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return data
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def hf_select(evt: gr.SelectData, data):
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return data[evt.index[0]][0]
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def hf_download_model(hub_id: str, token, variant, revision, mirror, custom_pipeline):
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hf_init()
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from modules.modelloader import download_diffusers_model
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download_diffusers_model(hub_id, cache_dir=opts.diffusers_dir, token=token, variant=variant, revision=revision, mirror=mirror, custom_pipeline=custom_pipeline)
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from modules.sd_models import list_models # pylint: disable=W0621
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list_models()
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log.info(f'Diffuser model downloaded: model="{hub_id}"')
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return f'Diffuser model downloaded: model="{hub_id}"'
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def hf_update_token(token):
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log.debug('Huggingface update token')
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opts.huggingface_token = token
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opts.save()
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