Instructions to use aymanashour/summ2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aymanashour/summ2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aymanashour/summ2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aymanashour/summ2") model = AutoModelForSequenceClassification.from_pretrained("aymanashour/summ2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20f363c9065101262f6ce2b6c30c041dc3cad2e7de1b83778169fc5a9ec50ff3
- Size of remote file:
- 2.84 GB
- SHA256:
- a329e5f56061cb456708c60ee0209cf456ce4c2851cb1fb387d5e3b4beecd964
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