Summarization
Transformers
PyTorch
English
bart
text2text-generation
sagemaker
Eval Results (legacy)
Instructions to use philschmid/bart-base-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/bart-base-samsum 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="philschmid/bart-base-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("philschmid/bart-base-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("philschmid/bart-base-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5acf8f7595fc9282357d0fea477903eaf13a00ee23d0df667b5b0e55de39de30
- Size of remote file:
- 2.35 kB
- SHA256:
- 7ce1e4b47d7e2bf2d0c8b8757cb9b372beec5d3906ba7d3437ae751ffd3c50ab
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