Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use scales-okn/ontology-memorandum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/ontology-memorandum with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scales-okn/ontology-memorandum")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/ontology-memorandum") model = AutoModelForSequenceClassification.from_pretrained("scales-okn/ontology-memorandum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9192d0f9ae660ddd05675bba9052ba7320d64cdcfb8b2328e4200d48a5aa076
- Size of remote file:
- 3.25 kB
- SHA256:
- 7373a117d36354230bfa2253b80c5a6fd9f0a364baf5ed3233b8460d62d748a9
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