Instructions to use nvidia/DAM-3B-Self-Contained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Describe Anything
How to use nvidia/DAM-3B-Self-Contained with Describe Anything:
# pip install git+https://github.com/NVlabs/describe-anything from huggingface_hub import snapshot_download from dam import DescribeAnythingModel snapshot_download(nvidia/DAM-3B-Self-Contained, local_dir="checkpoints") dam = DescribeAnythingModel( model_path="checkpoints", conv_mode="v1", prompt_mode="focal_prompt", )
- Notebooks
- Google Colab
- Kaggle
Upload llava_llama.py
Browse files- llava_llama.py +1 -1
llava_llama.py
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@@ -1209,7 +1209,7 @@ class LlavaMetaModel(ABC):
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# print(llm_cfg, vision_tower_cfg, mm_projector_cfg); input("DEBUG load_pretrained")
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with ContextManagers(
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[
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-
no_init_weights(
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]
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):
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vlm = cls(config, *args, **kwargs)
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# print(llm_cfg, vision_tower_cfg, mm_projector_cfg); input("DEBUG load_pretrained")
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with ContextManagers(
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[
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+
no_init_weights(),
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]
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):
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vlm = cls(config, *args, **kwargs)
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