Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use EMBO/sd-panelization-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/sd-panelization-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/sd-panelization-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/sd-panelization-v2") model = AutoModelForTokenClassification.from_pretrained("EMBO/sd-panelization-v2") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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"O": 0
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"layer_norm_eps": 1e-12,
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"max_position_embeddings":
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"max_length": 512,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"O": 0
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 514,
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"max_length": 512,
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"model_type": "roberta",
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"num_attention_heads": 12,
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