Instructions to use sshleifer/distilbart-cnn-12-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/distilbart-cnn-12-3 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="sshleifer/distilbart-cnn-12-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-3") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-12-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e8b9178e5629ed3dc778bdf99d40104681dbb257400316bb25b8938aab666c4
- Size of remote file:
- 1.02 GB
- SHA256:
- ff00fbbbba775cfd6f27e7ec08c29211ca4ab80d14ef1812fd98b7638d53a952
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