Instructions to use smc/electric_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smc/electric_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="smc/electric_2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("smc/electric_2") model = AutoModelForImageClassification.from_pretrained("smc/electric_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sebastián Medina commited on
Commit ·
28a3564
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Parent(s): f8107db
Update config.json
Browse files- config.json +2 -2
config.json
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "
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"1": "
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"image_size": 224,
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"initializer_range": 0.02,
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "pole",
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"1": "transformer"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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