Instructions to use sshleifer/distilbart-cnn-6-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/distilbart-cnn-6-6 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-6-6")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-6-6") model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-6-6", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6206752aab48379810e7bdfd317d2dcd18051aaf90352d1347774cd0d41e6136
- Size of remote file:
- 666 MB
- SHA256:
- fd1513a7c450cd27838c1d383f1223e73d496ca15180a8dd07bada39da46d1a1
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