Instructions to use google/pegasus-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/pegasus-large 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/pegasus-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/pegasus-large") model = AutoModelForSeq2SeqLM.from_pretrained("google/pegasus-large") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cc3628940e3d729846d169b9987165c17f6ad729da50cf8e8fcc535d78ccb95
- Size of remote file:
- 2.28 GB
- SHA256:
- f960b58b993a843e9894718b094eb272efd3e65c6daf3549ea8930c046a5374d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.