Instructions to use siddheshtv/BlockNet10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siddheshtv/BlockNet10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="siddheshtv/BlockNet10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import BlockNet10 model = BlockNet10.from_pretrained("siddheshtv/BlockNet10", dtype="auto") - Notebooks
- Google Colab
- Kaggle
siddheshtv commited on
Commit ·
919e3a0
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Parent(s): 4dd8f2f
update config
Browse files- config.json +2 -1
config.json
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{
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"architectures": ["BlockNet10"],
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"hidden_size": 1024,
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"num_classes": 10
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}
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{
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"architectures": ["BlockNet10"],
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"hidden_size": 1024,
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"num_classes": 10,
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"model_type": "custom_model"
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}
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