Summarization
Transformers
PyTorch
TensorBoard
Swedish
bart
text2text-generation
Eval Results (legacy)
Instructions to use Gabriel/bart-base-cnn-swe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gabriel/bart-base-cnn-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-swe")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gabriel/bart-base-cnn-swe") model = AutoModelForSeq2SeqLM.from_pretrained("Gabriel/bart-base-cnn-swe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Gabriel/bart-base-cnn-swe: direct link, hf CLI and curl.
- Browser
- Download file 2.23 MB
-
https://huggingface.co/Gabriel/bart-base-cnn-swe/resolve/refs%2Fpr%2F3/tokenizer.json
- Command line
-
hf download hf://Gabriel/bart-base-cnn-swe@refs/pr/3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Gabriel/bart-base-cnn-swe/resolve/refs%2Fpr%2F3/tokenizer.json
2.23 MB
File too large to display, you can check the raw version instead.