Summarization
Transformers
PyTorch
English
bigbird_pegasus
text2text-generation
Eval Results (legacy)
Instructions to use google/bigbird-pegasus-large-pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/bigbird-pegasus-large-pubmed 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="google/bigbird-pegasus-large-pubmed")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/bigbird-pegasus-large-pubmed") model = AutoModelForSeq2SeqLM.from_pretrained("google/bigbird-pegasus-large-pubmed", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08fd697f0ac2eee5280630df77b6555652a9edb2c7c963e7786a019cc8be4cf0
- Size of remote file:
- 2.31 GB
- SHA256:
- 52f2ed5790404860ca352a9572967a3e459662a10de13a52dda3805e94b1852c
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