Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use scales-okn/ontology-arbitration-motion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/ontology-arbitration-motion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scales-okn/ontology-arbitration-motion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/ontology-arbitration-motion") model = AutoModelForSequenceClassification.from_pretrained("scales-okn/ontology-arbitration-motion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
7cfc80a
1
Parent(s): 19db37b
Model save
Browse files- pytorch_model.bin +1 -1
- runs/Jun13_15-08-53_delilah/1655151048.5348725/events.out.tfevents.1655151048.delilah.1426637.1 +3 -0
- runs/Jun13_15-08-53_delilah/events.out.tfevents.1655151048.delilah.1426637.0 +3 -0
- runs/Jun13_15-08-53_delilah/events.out.tfevents.1655151233.delilah.1426637.2 +3 -0
- training_args.bin +1 -1
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