Summarization
Transformers
PyTorch
ONNX
Safetensors
bart
text2text-generation
Generated from Trainer
seq2seq
Eval Results (legacy)
Instructions to use AdamCodd/bart-large-cnn-samsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/bart-large-cnn-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="AdamCodd/bart-large-cnn-samsum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AdamCodd/bart-large-cnn-samsum") model = AutoModelForSeq2SeqLM.from_pretrained("AdamCodd/bart-large-cnn-samsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e7631587083705db43665ef84776eadc22f6e79598302d3c996639214b70b100
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size 1625423320
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