Summarization
Transformers
PyTorch
Safetensors
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use morenolq/bart-base-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morenolq/bart-base-xsum 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="morenolq/bart-base-xsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("morenolq/bart-base-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("morenolq/bart-base-xsum") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2055b6a7aa858a4d24ee06ab21ec6db260fedf34321f78cc67e2c4f170c92b7e
- Size of remote file:
- 558 MB
- SHA256:
- 602f10f233b62277b8e629e3b0d53c5e616ad9ea57164d53c00ca5fa6faf1d52
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