Instructions to use google/bigbird-pegasus-large-bigpatent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/bigbird-pegasus-large-bigpatent 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-bigpatent")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/bigbird-pegasus-large-bigpatent") model = AutoModelForSeq2SeqLM.from_pretrained("google/bigbird-pegasus-large-bigpatent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/bigbird-pegasus-large-bigpatent: direct link, hf CLI and curl.
- Browser
- Download file 2.31 GB
-
https://huggingface.co/google/bigbird-pegasus-large-bigpatent/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/bigbird-pegasus-large-bigpatent/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/bigbird-pegasus-large-bigpatent/resolve/main/pytorch_model.bin
2.31 GB
- Xet hash:
- 4113f6bd09c00fd9cabf8e6b235cc73fb0c51593346beacc13ce7872d91bf47a
- Size of remote file:
- 2.31 GB
- SHA256:
- 52a5b27a631d0ae2445e77ce97e9fcd7d13402079a741111eea024cc46e5c9d4
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