Instructions to use bayan10/summarization-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bayan10/summarization-model 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="bayan10/summarization-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bayan10/summarization-model") model = AutoModelForSeq2SeqLM.from_pretrained("bayan10/summarization-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0919cff09df7af7e0d6567efeae241e12b4b235fed131c0fcb38a44261b739a
- Size of remote file:
- 1.32 MB
- SHA256:
- cbb59d772bc9bb2da5dc4a73a00c61c0912c6d2596aad970fa2cd3d69898b245
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