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mod.py
CHANGED
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@@ -71,15 +71,17 @@ def get_repo_safetensors(repo_id: str):
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# Initialize the base model
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base_model = models[0]
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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-
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def change_base_model(repo_id: str, progress=gr.Progress(track_tqdm=True)):
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global pipe
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try:
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if not is_repo_name(repo_id) or not is_repo_exists(repo_id): return
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progress(0, f"Loading model: {repo_id}")
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clear_cache()
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pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
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progress(1, f"Model loaded: {repo_id}")
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except Exception as e:
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print(e)
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@@ -135,6 +137,7 @@ def fuse_loras(pipe, lorajson: list[dict]):
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#pipe.unload_lora_weights()
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fuse_loras.zerogpu = True
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# Initialize the base model
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base_model = models[0]
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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last_model = models[0]
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def change_base_model(repo_id: str, progress=gr.Progress(track_tqdm=True)):
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global pipe
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global last_model
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try:
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if repo_id == last_model or not is_repo_name(repo_id) or not is_repo_exists(repo_id): return
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progress(0, f"Loading model: {repo_id}")
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clear_cache()
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pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
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last_model = repo_id
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progress(1, f"Model loaded: {repo_id}")
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except Exception as e:
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print(e)
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#pipe.unload_lora_weights()
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change_base_model.zerogpu = True
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fuse_loras.zerogpu = True
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