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
- Xet hash:
- 6232e5e331e43fcb3a4e1cc7a1eab2d288f5637e4a03a407e6fa9bc7ef9d23f1
- Size of remote file:
- 3.63 kB
- SHA256:
- 21aaf697c75df65d2eb5be9345e37644ec11ebb0b553a0845420f15c7671808c
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