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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46f4e4942c5cab092594bfbcd76acbb84ab0234c4bf34547964f51f139ce73c1
- Size of remote file:
- 1.63 GB
- SHA256:
- 8e589ff34942ff07948bbce579cf701cc19e1bfe370f4e4afaf24484ca5d2a2b
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