Instructions to use nytkng/distilbart_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nytkng/distilbart_summarization 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="nytkng/distilbart_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nytkng/distilbart_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("nytkng/distilbart_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 984ffc3fbbc77dbb5d40f70787b060e64d1203bb8f1e7368326d31fc0ad5079a
- Size of remote file:
- 1.22 GB
- SHA256:
- d062f86450e497ba0aeb7a9097a5fb6e2aa3f4b9f6613c99365048cf02923d61
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