Instructions to use xtie/BART-PET-impression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xtie/BART-PET-impression 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/BART-PET-impression")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("xtie/BART-PET-impression") model = AutoModelForSeq2SeqLM.from_pretrained("xtie/BART-PET-impression") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a025b532a788529e120ff49c4585547f9e9ba9488e55b4fbe6ce750eb67e2e7b
- Size of remote file:
- 1.63 GB
- SHA256:
- 214762635335cb1a43a65417f4b3ce919168cd9cad990e63990d7416a94b26b7
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