Instructions to use Goud/AraBERT-summarization-goud with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Goud/AraBERT-summarization-goud with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="Goud/AraBERT-summarization-goud")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Goud/AraBERT-summarization-goud") model = AutoModelForSeq2SeqLM.from_pretrained("Goud/AraBERT-summarization-goud") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73dd6f6e3aa3fc83aebb2d08e04bee05ff3fa3be54849dfc875d50351c92be29
- Size of remote file:
- 1.2 GB
- SHA256:
- 836153e3b70819ee94bb4578111f2a108224367156eb8a25f8ca7bd92d06a6ff
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