Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use scales-okn/ontology-motion-to-certify-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scales-okn/ontology-motion-to-certify-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scales-okn/ontology-motion-to-certify-class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scales-okn/ontology-motion-to-certify-class") model = AutoModelForSequenceClassification.from_pretrained("scales-okn/ontology-motion-to-certify-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90c6ff91f7eae70e1473c2e2709e0061ced0b2e42b97bf77b1083da7bf5eaf26
- Size of remote file:
- 3.25 kB
- SHA256:
- 122b5e5f81b2c564c3a0ae08ef05415e850b2dcbebed423518486e1d52a0a512
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