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add an option to unload models during hypernetwork training to save VRAM
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@@ -201,7 +201,7 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
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return embedding, filename
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pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
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for i, (x, text) in pbar:
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for i, (x, text, _) in pbar:
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embedding.step = i + ititial_step
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if embedding.step > steps:
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