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
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README.md
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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## Model description
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It separates figure captions into their constituent panels.
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## Intended uses & limitations
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## Training and evaluation data
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Trained in in the [SourceData](https://huggingface.co/datasets/EMBO/sd-nlp-non-tokenized) dataset.
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## Training procedure
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