Summarization
Transformers
PyTorch
TensorBoard
Swedish
bart
text2text-generation
Eval Results (legacy)
Instructions to use Gabriel/bart-base-cnn-xsum-cite-swe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gabriel/bart-base-cnn-xsum-cite-swe 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="Gabriel/bart-base-cnn-xsum-cite-swe")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gabriel/bart-base-cnn-xsum-cite-swe") model = AutoModelForSeq2SeqLM.from_pretrained("Gabriel/bart-base-cnn-xsum-cite-swe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dec924b65f32fce13e57183aedc1d08b73f214acfdf864b23fb38d43367737cc
- Size of remote file:
- 3.57 kB
- SHA256:
- 86f4cd5b6126bdf935cb9bac3df8d4b2582a97b6d113515d13f18f43e2c94f68
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