Instructions to use aymanashour/summ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aymanashour/summ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aymanashour/summ")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aymanashour/summ") model = AutoModelForSequenceClassification.from_pretrained("aymanashour/summ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from aymanashour/summ: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/aymanashour/summ/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://aymanashour/summ/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aymanashour/summ/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 31f33893f8165c8b535d93b608b28d501ba87f9b229e5807dacc250f66d51fc8
- Size of remote file:
- 1.42 GB
- SHA256:
- 4ffb2f221c06f38c5f373625c62e75925dc347eb1e09368b5b28123898bafe3b
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