Instructions to use sshleifer/distilbart-cnn-12-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/distilbart-cnn-12-6 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-12-6")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-6") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-12-6") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12fafd1567394dd10c30d963d02ebf70568c2cd509bad3e0a6af52183d984b11
- Size of remote file:
- 1.22 GB
- SHA256:
- 3bac65d18c99463302d12ca75c2220ea714f9c81ce235f205fa818efe71df6ea
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