Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use scales-okn/ontology-proposed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/ontology-proposed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scales-okn/ontology-proposed")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/ontology-proposed") model = AutoModelForSequenceClassification.from_pretrained("scales-okn/ontology-proposed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
52c24ed
1
Parent(s): 01ef0eb
Model save
Browse files- pytorch_model.bin +1 -1
- runs/Apr02_23-39-15_delilah/1648960817.009542/events.out.tfevents.1648960817.delilah.3799582.1 +3 -0
- runs/Apr02_23-39-15_delilah/events.out.tfevents.1648960816.delilah.3799582.0 +3 -0
- runs/Apr02_23-39-15_delilah/events.out.tfevents.1648960930.delilah.3799582.2 +3 -0
- training_args.bin +1 -1
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