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infra for full-model load/save with quant
Signed-off-by: Vladimir Mandic <mandic00@live.com>
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@@ -589,6 +589,9 @@ def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", c
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negative_weights.pop(0)
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embedding_providers = prepare_embedding_providers(pipe, clip_skip)
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if len(embedding_providers) == 0:
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shared.log.error("Prompt encode: cannot find text encoder in model")
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return None, None, None, None, None, None
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empty_embedding_providers = None
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if 'StableCascade' in pipe.__class__.__name__:
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empty_embedding_providers = [embedding_providers[1]]
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