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", device_map="auto")# 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:
- 2bf91b8b4ef756df3cd2f888ceed6f5aeab07221e0143bcf0107a1d70bccf90c
- Size of remote file:
- 4.09 kB
- SHA256:
- 285838ad9dbad5b2fdafcee8ddc14e3c5034afbee30361c5a59a1d7afc8a6257
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