clarify print
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@@ -96,7 +96,7 @@ class DownloadAndLoadFlorence2Model:
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local_dir=model_path,
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local_dir_use_symlinks=False)
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print(f"using {attention} for attention")
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print(f"Florence2 using {attention} for attention")
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with patch("transformers.dynamic_module_utils.get_imports", fixed_get_imports): #workaround for unnecessary flash_attn requirement
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model = AutoModelForCausalLM.from_pretrained(model_path, attn_implementation=attention, device_map=device, torch_dtype=dtype,trust_remote_code=True)
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processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
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@@ -172,7 +172,7 @@ class Florence2ModelLoader:
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dtype = {"bf16": torch.bfloat16, "fp16": torch.float16, "fp32": torch.float32}[precision]
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model_path = Path(folder_paths.models_dir, "LLM", model)
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print(f"Loading model from {model_path}")
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print(f"using {attention} for attention")
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print(f"Florence2 using {attention} for attention")
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with patch("transformers.dynamic_module_utils.get_imports", fixed_get_imports): #workaround for unnecessary flash_attn requirement
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model = AutoModelForCausalLM.from_pretrained(model_path, attn_implementation=attention, device_map=device, torch_dtype=dtype,trust_remote_code=True)
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processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
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+1
-1
@@ -1,7 +1,7 @@
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[project]
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name = "comfyui-florence2"
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description = "Nodes to use Florence2 VLM for image vision tasks: object detection, captioning, segmentation and ocr"
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version = "1.0.2"
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version = "1.0.3"
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license = "MIT"
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dependencies = ["transformers>=4.38.0"]
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