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", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("morenolq/bart-base-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("morenolq/bart-base-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da055070e7069be235c2202623909ba649dfa16a7c8999d76b0ed4d2967a305d
- Size of remote file:
- 3.31 kB
- SHA256:
- 71d7ebc3b4dd387fdc49e43fffe2da800464dca38acee95aeb04653d5b910789
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