Instructions to use praf-choub/bart-CaPE-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praf-choub/bart-CaPE-xsum 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="praf-choub/bart-CaPE-xsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("praf-choub/bart-CaPE-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("praf-choub/bart-CaPE-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39732b8c4c5f6bf358143445680c843f8df090cc0be6625b62c8ec97833d0f2f
- Size of remote file:
- 2.24 GB
- SHA256:
- bb1c312f9c21d166741b75aa8978ceae1cbad15dbb7fee8d4c202a517718c683
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