Instructions to use praf-choub/bart-CaPE-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use praf-choub/bart-CaPE-cnn 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-cnn")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("praf-choub/bart-CaPE-cnn") model = AutoModelForSeq2SeqLM.from_pretrained("praf-choub/bart-CaPE-cnn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2fc18dbe23fc632deed7775a992cb3517fd1e3e4e5ce15e238e942b652d7ba8
- Size of remote file:
- 2.24 GB
- SHA256:
- c07e43e864ca5309585c11a2051ecf478b1b084a2a55151884018875073ad2cd
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