Instructions to use Eitanli/topic_abstract_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eitanli/topic_abstract_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Eitanli/topic_abstract_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Eitanli/topic_abstract_classification") model = AutoModelForSequenceClassification.from_pretrained("Eitanli/topic_abstract_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9f2d87e13f78068e9270879ee3f92e0b3e6ea10ae4796f0bafecbfeb94ae5f2
- Size of remote file:
- 438 MB
- SHA256:
- 1244624a0d7fcfa17f96053273b7e81f0524a5870bffc03ed9517400abfb2bed
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