Image Classification
Transformers
Safetensors
English
siglip
MINC
2500
Classification
Materials
Leather
Brick
Metal
Skin
Food
Stone
Instructions to use prithivMLmods/Minc-Materials-23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Minc-Materials-23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Minc-Materials-23") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Minc-Materials-23") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Minc-Materials-23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- mcimpoi/minc-2500_split_1
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language:
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- en
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base_model:
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- google/siglip2-base-patch16-224
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pipeline_tag: image-classification
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library_name: transformers
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tags:
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- MINC
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- '2500'
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- Classification
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- Materials
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- Leather
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- Brick
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- Metal
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- Skin
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- Food
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- Stone
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---
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