Instructions to use syscv-community/sam-hq-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syscv-community/sam-hq-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="syscv-community/sam-hq-vit-base")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("syscv-community/sam-hq-vit-base") model = AutoModelForMaskGeneration.from_pretrained("syscv-community/sam-hq-vit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +18 -0
- model.safetensors +3 -0
config.json
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{
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"architectures": [
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"SamHQModel"
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],
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"initializer_range": 0.02,
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"mask_decoder_config": {
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"model_type": ""
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},
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"model_type": "sam_hq",
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"prompt_encoder_config": {
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"model_type": ""
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},
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"torch_dtype": "float32",
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"transformers_version": "4.50.0.dev0",
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"vision_config": {
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"model_type": ""
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b3a4c62fa9ebff888b3a891010392b32233ec3dce12d2ece8e19c746ca71cb64
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size 379266384
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