Instructions to use opticalmaterials/opticalbert_abstract_classification_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opticalmaterials/opticalbert_abstract_classification_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="opticalmaterials/opticalbert_abstract_classification_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("opticalmaterials/opticalbert_abstract_classification_cased") model = AutoModelForSequenceClassification.from_pretrained("opticalmaterials/opticalbert_abstract_classification_cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
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