Instructions to use xtie/BARTScore-PET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtie/BARTScore-PET 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="xtie/BARTScore-PET")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("xtie/BARTScore-PET") model = AutoModelForSeq2SeqLM.from_pretrained("xtie/BARTScore-PET", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55b5572d22af4b175dcfe07d0cda3c507c5f01db9c88e3cabe40abd8bb3f25a5
- Size of remote file:
- 1.63 GB
- SHA256:
- 079fff8c82d2d512504ffc9615dc42093b132e11ad8d74d2087496c1c96c58e9
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