39 lines
1.3 KiB
Python
Executable File
39 lines
1.3 KiB
Python
Executable File
# import html
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#
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# import gradio as gr
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#
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# import modules.textual_inversion.textual_inversion
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# from modules import sd_hijack, shared
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#
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#
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# def create_embedding(name, initialization_text, nvpt, overwrite_old):
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# filename = modules.textual_inversion.textual_inversion.create_embedding(name, nvpt, overwrite_old, init_text=initialization_text)
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#
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# sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
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#
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# return gr.Dropdown.update(choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())), f"Created: {filename}", ""
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#
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#
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# def train_embedding(*args):
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#
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# assert not shared.cmd_opts.lowvram, 'Training models with lowvram not possible'
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#
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# apply_optimizations = shared.opts.training_xattention_optimizations
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# try:
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# if not apply_optimizations:
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# sd_hijack.undo_optimizations()
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#
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# embedding, filename = modules.textual_inversion.textual_inversion.train_embedding(*args)
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#
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# res = f"""
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# Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
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# Embedding saved to {html.escape(filename)}
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# """
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# return res, ""
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# except Exception:
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# raise
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# finally:
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# if not apply_optimizations:
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# sd_hijack.apply_optimizations()
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#
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