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:
- 10325b2a5caf2aac0623a00dbeb4623e9970a9066524f6f4f644bd08cab9e888
- Size of remote file:
- 1.42 GB
- SHA256:
- c8866eac1ed2fe02adb82c8a56059b06e7dfa3c3f6ddf43b119724db2a779675
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