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")# pip install -U transformers accelerate # 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
Download optimizer.pt from aymanashour/summ2: direct link, hf CLI and curl.
- Browser
- Download file 2.84 GB
-
https://huggingface.co/aymanashour/summ2/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://aymanashour/summ2@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/aymanashour/summ2/resolve/refs%2Fpr%2F1/optimizer.pt
2.84 GB
- Xet hash:
- 20f363c9065101262f6ce2b6c30c041dc3cad2e7de1b83778169fc5a9ec50ff3
- Size of remote file:
- 2.84 GB
- SHA256:
- a329e5f56061cb456708c60ee0209cf456ce4c2851cb1fb387d5e3b4beecd964
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