Instructions to use eslamxm/AraBART-finetuned-ar-wikilingua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eslamxm/AraBART-finetuned-ar-wikilingua 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="eslamxm/AraBART-finetuned-ar-wikilingua")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("eslamxm/AraBART-finetuned-ar-wikilingua") model = AutoModelForSeq2SeqLM.from_pretrained("eslamxm/AraBART-finetuned-ar-wikilingua", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from eslamxm/AraBART-finetuned-ar-wikilingua: direct link, hf CLI and curl.
- Browser
- Download file 3.78 MB
-
https://huggingface.co/eslamxm/AraBART-finetuned-ar-wikilingua/resolve/main/tokenizer.json
- Command line
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hf download hf://eslamxm/AraBART-finetuned-ar-wikilingua/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/eslamxm/AraBART-finetuned-ar-wikilingua/resolve/main/tokenizer.json
3.78 MB
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